Posts Tagged ‘commerce’

Reimagining Capitalism Again, Part I: Reflections on Greider’s Soul of Capitalism

September 10, 2011

In his 2003 book, The Soul of Capitalism, William Greider wrote, “If capitalism were someday found to have a soul, it would probably be located in the mystic qualities of capital itself” (p. 94). The recurring theme in the book is that the resolution of capitalism’s deep conflicts must grow out as organic changes from the roots of capitalism itself.

In the book, Greider quotes Innovest’s Michael Kiernan as suggesting that the goal has to be re-engineering the DNA of Wall Street (p. 119). He says the key to doing this is good reliable information that has heretofore been unavailable but which will make social and environmental issues matter financially. The underlying problems of exactly what solid, high quality information looks like, where it comes from, and how it is created are not stated or examined, but the point, as Kiernan says, is that “the markets are pretty good at punishing and rewarding.” The objective is to use “the financial markets as an engine of reform and positive change rather than destruction.”

This objective is, of course, the focus of multiple postings in this blog (see especially this one and this one). From my point of view, capitalism indeed does have a soul and it is actually located in the qualities of capital itself. Think about it: if a soul is a spirit of something that exists independent of its physical manifestation, then the soul of capitalism is the fungibility of capital. Now, this fungibility is complex and ambiguous. It takes its strength and practical value from the way market exchange are represented in terms of currencies, monetary units that, within some limits, provide an objective basis of comparison useful for rewarding those capable of matching supply with demand.

But the fungibility of capital can also be dangerously misconceived when the rich complexity and diversity of human capital is unjustifiably reduced to labor, when the irreplaceable value of natural capital is unjustifiably reduced to land, and when the trust, loyalty, and commitment of social capital is completely ignored in financial accounting and economic models. As I’ve previously said in this blog, the concept of human capital is inherently immoral so far as it reduces real human beings to interchangeable parts in an economic machine.

So how could it ever be possible to justify any reduction of human, social, and natural value to a mere number? Isn’t this the ultimate in the despicable inhumanity of economic logic, corporate decision making, and, ultimately, the justification of greed? Many among us who profess liberal and progressive perspectives seem to have an automatic and reactionary prejudice of this kind. This makes these well-intentioned souls as much a part of the problem as those among us with sometimes just as well-intentioned perspectives that accept such reductionism as the price of entry into the game.

There is another way. Human, social, and natural value can be measured and made manageable in ways that do not necessitate totalizing reduction to a mere number. The problem is not reduction itself, but unjustified, totalizing reduction. Referring to all people as “man” or “men” is an unjustified reduction dangerous in the way it focuses attention only on males. The tendency to think and act in ways privileging males over females that is fostered by this sense of “man” shortchanges us all, and has happily been largely eliminated from discourse.

Making language more inclusive does not, however, mean that words lose the singular specificity they need to be able to refer to things in the world. Any given word represents an infinite population of possible members of a class of things, actions, and forms of life. Any simple sentence combining words into a coherent utterance then multiplies infinities upon infinities. Discourse inherently reduces multiplicities into texts of limited lengths.

Like any tool, reduction has its uses. Also like any tool, problems arise when the tool is allowed to occupy some hidden and unexamined blind spot from which it can dominate and control the way we think about everything. Critical thinking is most difficult in those instances in which the tools of thinking themselves need to be critically evaluated. To reject reduction uncritically as inherently unjustified is to throw the baby out with the bathwater. Indeed, it is impossible to formulate a statement of the rejection without simultaneously enacting exactly what is supposed to be rejected.

We have numerous ready-to-hand examples of how all reduction has been unjustifiably reduced to one homogenized evil. But one of the results of experiments in communal living in the 1960s and 1970s, as well as of the fall of the Soviet Union, was the realization that the centralized command and control of collectively owned community property cannot compete with the creativity engendered when individuals hold legal title to the fruits of their labors. If individuals cannot own the results of the investments they make, no one makes any investments.

In other words, if everything is owned collectively and is never reduced to individually possessed shares that can be creatively invested for profitable returns, then the system is structured so as to punish innovation and reward doing as little as possible. But there’s another way of thinking about the relation of the collective to the individual. The living soul of capitalism shows itself in the way high quality information makes it possible for markets to efficiently coordinate and align individual producers’ and consumers’ collective behaviors and decisions. What would happen if we could do that for human, social, and natural capital markets? What if “social capitalism” is more than an empty metaphor? What if capital institutions can be configured so that individual profit really does become the driver of socially responsible, sustainable economics?

And here we arrive at the crux of the problem. How do we create the high quality, solid information markets need to punish and reward relative to ethical and sustainable human, social, and environmental values? Well, what can we learn from the way we created that kind of information for property and manufactured capital? These are the questions taken up and explored in the postings in this blog, and in my scientific research publications and meeting presentations. In the near future, I’ll push my reflection on these questions further, and will explore some other possible answers to the questions offered by Greider and his readers in a recent issue of The Nation.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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New Opportunities for Job Creation and Prosperity

August 17, 2011

What can be done to create jobs and revive the economy? There is no simple, easy answer to this question. Creating busywork is nonsense. We need fulfilling occupations that meet the world’s demand for products and services. It is not easy to see how meaningful work can be systematically created on a broad scale. New energy efficiencies may lead to the cultivation of significant job growth, but it may be unwise to put all of our eggs in this one basket.

So how are we to solve this puzzle? What other areas in the economy might be ripe for the introduction of a new technology capable of supporting a wave of new productivity, like computers did in the 1980s, or the Internet in the 1990s? In trying to answer this question, simplicity and elegance are key factors in keeping things at a practical level.

For instance, we know we accomplish more working together as a team than as disconnected individuals. New jobs, especially new kinds of jobs, will have to be created via innovation. Innovation in science and industry is a team sport. So the first order of business in teaming up for job creation is to know the rules of the game. The economic game is played according to the rules of law embodied in property rights, scientific rationality, capital markets, and transportation/communications networks (see William Bernstein’s 2004 book, The Birth of Plenty). When these conditions are met, as they were in Europe and North America at the beginning of the nineteenth century, the stage is set for long term innovation and growth on a broad scale.

The second order of business is to identify areas in the economy that lack one or more of these four conditions, and that could reasonably be expected to benefit from their introduction. Education, health care, social services, and environmental management come immediately to mind. These industries are plagued with seemingly interminable inflationary spirals, which, no doubt, are at least in part caused by the inability of investors to distinguish between high and low performers. Money cannot flow to and reward programs producing superior results in these industries because they lack common product definitions and comparable measures of their results.

The problems these industries are experiencing are not specific to each of them in particular. Rather, the problem is a general one applicable across all industries, not just these. Traditionally, economic thinking focuses on three main forms of capital: land, labor, and manufactured products (including everything from machines, roads, and buildings to food, clothing, and appliances). Cash and credit are often thought of as liquid capital, but their economic value stems entirely from the access they provide to land, labor, and manufactured products.

Economic activity is not really, however, restricted to these three forms of capital. Land is far more than a piece of ground. What are actually at stake are the earth’s regenerative ecosystems, with the resources and services they provide. And labor is far more than a pair of skilled hands; people bring a complex mix of abilities, motivations, and health to bear in their work. Finally, this scheme lacks an essential element: the trust, loyalty, and commitment required for even the smallest economic exchange to take place. Without social capital, all the other forms of capital (human, natural, and manufactured, including property) are worthless. Consistent, sustainable, and socially responsible economic growth requires that all four forms of capital be made accountable in financial spreadsheets and economic models.

The third order of business, then, is to ask if the four conditions laying out the rules for the economic game are met in each of the four capital domains. The table below suggests that all four conditions are fully met only for manufactured products. They are partially met for natural resources, such as minerals, timber, fisheries, etc., but not at all for nature’s air and water purification systems or broader genetic ecosystem services.

 Table

Existing Conditions Relevant to Conceiving a New Birth of Plenty, by Capital Domains

Human

Social

Natural

Manufactured

Property rights

No

No

Partial

Yes

Scientific rationality

Partial

Partial

Partial

Yes

Capital markets

Partial

Partial

Partial

Yes

Transportation & communication networks

Partial

Partial

Partial

Yes

That is, no provisions exist for individual ownership of shares in the total available stock of air and water, or of forest, watershed, estuary, and other ecosystem service outcomes. Nor do any individuals have free and clear title to their most personal properties, the intangible abilities, motivations, health, and trust most essential to their economic productivity. Aggregate statistics are indeed commonly used to provide a basis for policy and research in human, social, and natural capital markets, but falsifiable models of individually applicable unit quantities are not widely applied. Scientifically rational measures of our individual stocks of intangible asset value will require extensive use of these falsifiable models in calibrating the relevant instrumentation.

Without such measures, we cannot know how many shares of stock in these forms of capital we own, or what they are worth in dollar terms. We lack these measures, even though decades have passed since researchers first established firm theoretical and practical foundations for them. And more importantly, even when scientifically rational individual measures can be obtained, they are never expressed in terms of a unit standardized for use within a given market’s communications network.

So what are the consequences for teams playing the economic game? High performance teams’ individual decisions and behaviors are harmonized in ways that cannot otherwise be achieved only when unit amounts, prices, and costs are universally comparable and publicly available. This is why standard currencies and exchange rates are so important.

And right here we have an insight into what we can do to create jobs. New jobs are likely going to have to be new kinds of jobs resulting from innovations. As has been detailed at length in recent works such as Surowiecki’s 2004 book, The Wisdom of Crowds, innovation in science and industry depends on standards. Standards are common languages that enable us to multiply our individual cognitive powers into new levels of collective productivity. Weights and measures standards are like monetary currencies; they coordinate the exchange of value in laboratories and businesses in the same way that dollars do in the US economy.

Applying Bernstein’s four conditions for economic growth to intangible assets, we see that a long term program for job creation then requires

  1. legislation establishing human, social, and natural capital property rights, and an Intangible Assets Metrology System;
  2. scientific research into consensus standards for measuring human, social, and natural capital;
  3. venture capital educational and marketing programs; and
  4. distributed information networks and computer applications through which investments in human, social, and natural capital can be tracked and traded in accord with the rule of law governing property rights and in accord with established consensus standards.

Of these four conditions, Bernstein (p. 383) points to property rights as being the most difficult to establish, and the most important for prosperity. Scientific results are widely available in online libraries. Capital can be obtained from investors anywhere. Transportation and communications services are available commercially.

But valid and verifiable means of representing legal title to privately owned property is a problem often not yet solved even for real estate in many Third World and former communist countries (see De Soto’s 2000 book, The Mystery of Capital). Creating systems for knowing the quality and quantity of educational, health care, social, and environmental service outcomes is going to be a very difficult process. It will not be impossible, however, and having the problem identified advances us significantly towards new economic possibilities.

We need leaders able and willing to formulate audacious goals for new economic growth from ideas such as these. We need enlightened visionaries able to see our potentials from a new perspective, and who can reflect our new self-image back at us. When these leaders emerge—and they will, somewhere, somehow—the imaginations of millions of entrepreneurial thinkers and actors will be fired, and new possibilities will unfold.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Science, Public Goods, and the Monetization of Commodities

August 13, 2011

Though I haven’t read Philip Mirowski’s new book yet (Science-Mart: Privatizing American Science. Cambridge, MA: Harvard University Press, 2011), a statement in the cover blurb given at Amazon.com got me thinking. I can’t help but wonder if there is another way of interpreting neoliberal ideology’s “radically different view of knowledge and discovery: [that] the fruits of scientific investigation are not a public good that should be freely available to all, but are commodities that could be monetized”?

Corporations and governments are not the only ones investing in research and new product development, and they are not the only ones who could benefit from the monetization of the fruits of scientific investigation. Individuals make these investments as well, and despite ostensible rights to private ownership, no individuals anywhere have access to universally comparable, uniformly expressed, and scientifically valid information on the quantity or quality of the literacy, health, community, or natural capital that is rightfully theirs. They accordingly also then do not have any form of demonstrable legal title to these properties. In the same way that corporations have successfully advanced their economic interests by seeing that patent and intellectual property laws were greatly strengthened, so, too, ought individuals and communities advance their economic interests by, first, expanding the scope of weights and measures standards to include intangible assets, and second, by strengthening laws related to the ownership of privately held stocks of living capital.

The nationalist and corporatist socialization of research will continue only as long as social capital, human capital, and natural capital are not represented in the universally uniform common currencies and transparent media that could be provided by an intangible assets metric system. When these forms of capital are brought to economic life in fungible measures akin to barrels, bushels, or kilowatts, then they will be monetized commodities in the full capitalist sense of the term, ownable and purchasable products with recognizable standard definitions, uniform quantitative volumes, and discernable variations in quality. Then, and only then, will individuals gain economic control over their most important assets. Then, and only then, will we obtain the information we need to transform education, health care, social services, and human and natural resource management into industries in which quality is appropriately rewarded. Then, and only then, will we have the means for measuring genuine progress and authentic wealth in ways that correct the insufficiencies of the GNP/GDP indexes.

The creation of efficiently functioning markets for all forms of capital is an economic, political, and moral necessity (see Ekins, 1992 and others). We say we manage what we measure, but very little effort has been put into measuring (with scientific validity and precision in universally uniform and accessible aggregate terms) 90% of the capital resources under management: human abilities, motivations, and health; social commitment, loyalty, and trust; and nature’s air and water purification and ecosystem services (see Hawken, Lovins, & Lovins, 1999, among others). All human suffering, sociopolitical discontent, and environmental degradation are rooted in the same common cause: waste (see Hawken, et al., 1999). To apply lean thinking to removing the wasteful destruction of our most valuable resources, we must measure these resources in ways that allow us to coordinate and align our decisions and behaviors virtually, at a distance, with no need for communicating and negotiating the local particulars of the hows and whys of our individual situations. For more information on these ideas, search “living capital metrics” and see works like the following:

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-15). London: Routledge.

Fisher, W. P., Jr. (2009). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Hawken, P., Lovins, A., & Lovins, H. L. (1999). Natural capitalism: Creating the next industrial revolution. New York: Little, Brown, and Co.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Latour, B. (2005). Reassembling the social: An introduction to Actor-Network-Theory. (Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

Miller, P., & O’Leary, T. (2007). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-34.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Debt, Revenue, and Changing the Way Washington Works: The Greatest Entrepreneurial Opportunity of Our Time

July 30, 2011

“Holding the line” on spending and taxes does not make for a fundamental transformation of the way Washington works. Simply doing less of one thing is just a small quantitative change that does nothing to build positive results or set a new direction. What we need is a qualitative metamorphosis akin to a caterpillar becoming a butterfly. In contrast with this beautiful image of natural processes, the arguments and so-called principles being invoked in the sham debate that’s going on are nothing more than fights over where to put deck chairs on the Titanic.

What sort of transformation is possible? What kind of a metamorphosis will start from who and where we are, but redefine us sustainably and responsibly? As I have repeatedly explained in this blog, my conference presentations, and my publications, with numerous citations of authoritative references, we already possess all of the elements of the transformation. We have only to organize and deploy them. Of course, discerning what the resources are and how to put them together is not obvious. And though I believe we will do what needs to be done when we are ready, it never hurts to prepare for that moment. So here’s another take on the situation.

Infrastructure that supports lean thinking is the name of the game. Lean thinking focuses on identifying and removing waste. Anything that consumes resources but does not contribute to the quality of the end product is waste. We have enormous amounts of wasteful inefficiency in many areas of our economy. These inefficiencies are concentrated in areas in which management is hobbled by low quality information, where we lack the infrastructure we need.

Providing and capitalizing on this infrastructure is The Greatest Entrepreneurial Opportunity of Our Time. Changing the way Washington (ha! I just typed “Wastington”!) works is the same thing as mitigating the sources of risk that caused the current economic situation. Making government behave more like a business requires making the human, social, and natural capital markets more efficient. Making those markets more efficient requires reducing the costs of transactions. Those costs are determined in large part by information quality, which is a function of measurement.

It is often said that the best way to reduce the size of government is to move the functions of government into the marketplace. But this proposal has never been associated with any sense of the infrastructural components needed to really make the idea work. Simply reducing government without an alternative way of performing its functions is irresponsible and destructive. And many of those who rail on and on about how bad or inefficient government is fail to recognize that the government is us. We get the government we deserve. The government we get follows directly from the kind of people we are. Government embodies our image of ourselves as a people. In the US, this is what having a representative form of government means. “We the people” participate in our society’s self-governance not just by voting, writing letters to congress, or demonstrating, but in the way we spend our money, where we choose to live, work, and go to school, and in every decision we make. No one can take a breath of air, a drink of water, or a bite of food without trusting everyone else to not carelessly or maliciously poison them. No one can buy anything or drive down the street without expecting others to behave in predictable ways that ensure order and safety.

But we don’t just trust blindly. We have systems in place to guard against those who would ruthlessly seek to gain at everyone else’s expense. And systems are the point. No individual person or firm, no matter how rich, could afford to set up and maintain the systems needed for checking and enforcing air, water, food, and workplace safety measures. Society as a whole invests in the infrastructure of measures created, maintained, and regulated by the government’s Department of Commerce and the National Institute for Standards and Technology (NIST). The moral importance and the economic value of measurement standards has been stressed historically over many millennia, from the Bible and the Quran to the Magna Carta and the French Revolution to the US Constitution. Uniform weights and measures are universally recognized and accepted as essential to fair trade.

So how is it that we nonetheless apparently expect individuals and local organizations like schools, businesses, and hospitals to measure and monitor students’ abilities; employees’ skills and engagement; patients’ health status, functioning, and quality of care; etc.? Why do we not demand common currencies for the exchange of value in human, social, and natural capital markets? Why don’t we as a society compel our representatives in government to institute the will of the people and create new standards for fair trade in education, health care, social services, and environmental management?

Measuring better is not just a local issue! It is a systemic issue! When measurement is objective and when we all think together in the common language of a shared metric (like hours, volts, inches or centimeters, ounces or grams, degrees Fahrenheit or Celsius, etc.), then and only then do we have the means we need to implement lean strategies and create new efficiencies systematically. We need an Intangible Assets Metric System.

The current recession in large part was caused by failures in measuring and managing trust, responsibility, loyalty, and commitment. Similar problems in measuring and managing human, social, and natural capital have led to endlessly spiraling costs in education, health care, social services, and environmental management. The problems we’re experiencing in these areas are intimately tied up with the way we formulate and implement group level decision making processes and policies based in statistics when what we need is to empower individuals with the tools and information they need to make their own decisions and policies. We will not and cannot metamorphose from caterpillar to butterfly until we create the infrastructure through which we each can take full ownership and control of our individual shares of the human, social, and natural capital stock that is rightfully ours.

We well know that we manage what we measure. What counts gets counted. Attention tends to be focused on what we’re accountable for. But–and this is vitally important–many of the numbers called measures do not provide the information we need for management. And not only are lots of numbers giving us low quality information, there are far too many of them! We could have better and more information from far fewer numbers.

Previous postings in this blog document the fact that we have the intellectual, political, scientific, and economic resources we need to measure and manage human, social, and natural capital for authentic wealth. And the issue is not a matter of marshaling the will. It is hard to imagine how there could be more demand for better management of intangible assets than there is right now. The problem in meeting that demand is a matter of imagining how to start the ball rolling. What configuration of investments and resources will start the process of bursting open the chrysalis? How will the demand for meaningful mediating instruments be met in a way that leads to the spreading of the butterfly’s wings? It is an exciting time to be alive.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Subjectivity, Objectivity, Performance Measurement and Markets

April 23, 2011

Though he attributes his insight to a colleague (George Baker), Michael Jensen has once more succinctly stated a key point I’ve repeatedly tried to convey in my blog posts. As Jensen (2003, p. 397) puts it,

…any activity whose performance can be perfectly measured objectively does not belong inside the firm. If its performance can be adequately measured objectively it can be spun out of the firm and contracted for in a market transaction.

YES!! Though nothing is measured perfectly, my message has been a series of variations on precisely this theme. Well-measured property, services, products, and commodities in today’s economy are associated with scientific, legal and financial structures and processes that endow certain representations with meaningful indications of kind, amount, value and ownership. It is further well established that the ownership of the products of one’s creative endeavors is essential to economic advancement and the enlargement of the greater good. Markets could not exist without objective measures, and thus we have the central commercial importance of metric standards.

The improved measurement of service outcomes and performances is going to create an environment capable of supporting similar legal and financial indications of value and ownership. Many of the causes of today’s economic crises can be traced to poor quality information and inadequate measures of human, social, and natural value. Bringing publicly verifiable scientific data and methods to bear on the tuning of instruments for measuring these forms of value will make their harmonization much simpler than it ever could be otherwise. Social and environmental costs and value have been relegated to the marginal status of externalities because they have not been measured in ways that made it possible to bring them onto the books and into the models.

But the stage is being set for significant changes. Decades of research calibrating objective measures of a wide variety of performances and outcomes are inexorably leading to the creation of an intangible assets metric system (Fisher, 2009a, 2009b, 2011). Meaningful and rigorous individual-level universally available uniform metrics for each significant intangible asset (abilities, health, trustworthiness, etc.) will

(a) make it possible for each of us to take full possession, ownership, and management control of our investments in and returns from these forms of capital,

(b) coordinate the decisions and behaviors of consumers, researchers, and quality improvement specialists to better match supply and demand, and thereby

(c) increase the efficiency of human, social, and natural capital markets, harnessing the profit motive for the removal of wasted human potential, lost community coherence, and destroyed environmental quality.

Jensen’s observation emerges in his analysis of performance measures as one of three factors in defining the incentives and payoffs for a linear compensation plan (the other two being the intercept and the slope of the bonus line relating salary and bonus to the performance measure targets). The two sentences quoted above occur in this broader context, where Jensen (2003, pp. 396-397) states that,

…we must decide how much subjectivity will be involved in each performance measure. In considering this we must recognize that every performance measurement system in a firm must involve an important amount of subjectivity. The reason, as my colleague George Baker has pointed out, is that any activity whose performance can be perfectly measured objectively does not belong inside the firm. If its performance can be adequately measured objectively it can be spun out of the firm and contracted for in a market transaction. Thus, one of the most important jobs of managers, complementing objective measures of performance with managerial subjective evaluation of subtle interdependencies and other factors is exactly what most managers would like to avoid. Indeed, it is this factor along with efficient risk bearing that is at the heart of what gives managers and firms an advantage over markets.

Jensen is here referring implicitly to the point Coase (1990) makes regarding the nature of the firm. A firm can be seen as a specialized market, one in which methods, insights, and systems not generally available elsewhere are employed for competitive advantage. Products are brought to market competitively by being endowed with value not otherwise available. Maximizing that value is essential to the viability of the firm.

Given conflicting incentives and the mixed messages of the balanced scorecard, managers have plenty of opportunities for creatively avoiding the difficult task of maximizing the value of the firm. Jensen (2001) shows that attending to the “managerial subjective evaluation of subtle interdependencies” is made impossibly complex when decisions and behaviors are pulled in different directions by each stakeholder’s particular interests. Other research shows that even traditional capital structures are plagued by the mismeasurement of leverage, distress costs, tax shields, and the speed with which individual firms adjust their capital needs relative to leverage targets (Graham & Leary, 2010). The objective measurement of intangible assets surely seems impossibly complex to those familiar with these problems.

But perhaps the problems associated with measuring traditional capital structures are not so different from those encountered in the domain of intangible assets. In both cases, a particular kind of unjustified self-assurance seems always to attend the mere availability of numeric data. To the unpracticed eye, numbers seem to always behave the same way, no matter if they are rigorous measures of physical commodities, like kilowatts, barrels, or bushels, or if they are currency units in an accounting spreadsheet, or if they are percentages of agreeable responses to a survey question. The problem is that, when interrogated in particular ways with respect to the question of how much of something is supposedly measured, these different kinds of numbers give quite markedly different kinds of answers.

The challenge we face is one of determining what kind of answers we want to the questions we have to ask. Presumably, we want to ask questions and get answers pertinent to obtaining the information we need to manage life creatively, meaningfully, effectively and efficiently. It may be useful then, as a kind of thought experiment, to make a bold leap and imagine a scenario in which relevant questions are answered with integrity, accountability, and transparency.

What will happen when the specialized expertise of human resource professionals is supplanted by a market in which meaningful and comparable measures of the hireability, retainability, productivity, and promotability of every candidate and employee are readily available? If Baker and Jensen have it right, perhaps firms will no longer have employees. This is not to say that no one will work for pay. Instead, firms will contract with individual workers at going market rates, and workers will undoubtedly be well aware of the market value of their available shares of their intangible assets.

A similar consequence follows for the social safety net and a host of other control, regulatory, and policing mechanisms. But we will no longer be stuck with blind faith in the invisible hand and market efficiency, following the faith of those willing to place their trust and their futures in the hands of mechanisms they only vaguely understand and cannot control. Instead, aggregate effects on individuals, communities, and the environment will be tracked in publicly available and critically examined measures, just as stocks, bonds, and commodities are tracked now.

Previous posts in this blog explore the economic possibilities that follow from having empirically substantiated, theoretically predictable, and instrumentally mediated measures embodying broad consensus standards. What we will have for human, social, and natural capital will be the same kind of objective measures that have made markets work as well as they have thus far. It will be a whole new ball game when profits become tied to human, social, and environmental outcomes.

References

Coase, R. (1990). The firm, the market, and the law. Chicago: University of Chicago Press.

Fisher, W. P., Jr. (2009a, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P.. Jr. (2009b). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (Tech. Rep. No. http://www.livingcapitalmetrics.com/images/FisherNISTWhitePaper2.pdf). New Orleans: LivingCapitalMetrics.com.

Fisher, W. P., Jr. (2010, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities. Available at http://ssrn.com/abstract=1713467.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), in press.

Graham, J. R., & Leary, M. T. (2010, 21 December). A review of empirical capital structure research and directions for the future. Available at http://ssrn.com/abstract=1729388.

Jensen, M. C. (2001, Fall). Value maximization, stakeholder theory, and the corporate objective function. Journal of Applied Corporate Finance, 14(3), 8-21.

Jensen, M. C. (2003). Paying people to lie: The truth about the budgeting process. European Financial Management, 9(3), 379-406.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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The Moral Implications of the Concept of Human Capital: More on How to Create Living Capital Markets

March 22, 2011

The moral reprehensibility of the concept of human capital hinges on its use in rationalizing impersonal business decisions in the name of profits. Even when the viability of the organization is at stake, the discarding of people (referred to in some human resource departments as “taking out the trash”) entails degrees of psychological and economic injury no one should have to suffer, or inflict.

There certainly is a justified need for a general concept naming the productive capacity of labor. But labor is far more than a capacity for work. No one’s working life should be reduced to a job description. Labor involves a wide range of different combinations of skills, abilities, motivations, health, and trustworthiness. Human capital has then come to be broken down into a wide variety of forms, such as literacy capital, health capital, social capital, etc.

The metaphoric use of the word “capital” in the phrase “human capital” referring to stocks of available human resources rings hollow. The traditional concept of labor as a form of capital is an unjustified reduction of diverse capacities in itself. But the problem goes deeper. Intangible resources like labor are not represented and managed in the forms that make markets for tangible resources efficient. Transferable representations, like titles and deeds, give property a legal status as owned and an economic status as financially fungible. And in those legal and economic terms, tangible forms of capital give capitalism its hallmark signification as the lifeblood of the cycle of investment, profits, and reinvestment.

Intangible forms of capital, in contrast, are managed without the benefit of any standardized way of proving what is owned, what quantity or quality of it exists, and what it costs. Human, social, and natural forms of capital are therefore managed directly, by acting in an unmediated way on whomever or whatever embodies them. Such management requires, even in capitalist economies, the use of what are inherently socialistic methods, as these are the only methods available for dealing with the concrete individual people, communities, and ecologies involved (Fisher, 2002, 2011; drawing from Hayek, 1948, 1988; De Soto, 2000).

The assumption that transferable representations of intangible assets are inconceivable or inherently reductionist is, however, completely mistaken. All economic capital is ultimately brought to life (conceived, gestated, midwifed, and nurtured to maturity) as scientific capital. Scientific measurability is what makes it possible to add up the value of shares of stock across holdings, to divide something owned into shares, and to represent something in a court or a bank in a portable form (Latour, 1987; Fisher, 2002, 2011).

Only when you appreciate this distinction between dead and living capital, between capital represented on transferable instruments and capital that is not, then you can see that the real tragedy is not in the treatment of labor as capital. No, the real tragedy is in the way everyone is denied the full exercise of their rights over the skills, abilities, health, motivations, trustworthiness, and environmental resources that are rightly their own personal, private property.

Being homogenized at the population level into an interchangeable statistic is tragic enough. But when we leave the matter here, we fail to see and to grasp the meaning of the opportunities that are lost in that myopic world view. As I have been at pains in this blog to show, statistics are not measures. Statistical models of interactions between several variables at the group level are not the same thing as measurement models of interactions within a single variable at the individual level. When statistical models are used in place of measurement models, the result is inevitably numbers without a soul. When measurement models of individual response processes are used to produce meaningful estimates of how much of something someone possesses, a whole different world of possibilities opens up.

In the same way that the Pythagorean Theorem applies to any triangle, so, too, do the coordinates from the international geodetic survey make it possible to know everything that needs to be known about the location and disposition of a piece of real estate. Advanced measurement models in the psychosocial sciences are making it possible to arrive at similarly convenient and objective ways of representing the quality and quantity of intangible assets. Instead of being just one number among many others, real measures tell a story that situates each of us relative to everyone else in a meaningful way.

The practical meaning of the maxim “you manage what you measure” stems from those instances in which measures embody the fullness of the very thing that is the object of management interest. An engine’s fuel efficiency, or the volume of commodities produced, for instance, are things that can be managed less or more efficiently because there are measures of them that directly represent just what we want to control. Lean thinking enables the removal of resources that do not contribute to the production of the desired end result.

Many metrics, however, tend to obscure and distract from what need to be managed. The objects of measurement may seem to be obviously related to what needs to be managed, but dealing with each of them piecemeal results in inefficient and ineffective management. In these instances, instead of the characteristic cycle of investment, profit, and reinvestment, there seems only a bottomless pit absorbing ever more investment and never producing a profit. Why?

The economic dysfunctionality of intangible asset markets is intimately tied up with the moral dysfunctionality of those markets. Drawing an analogy from a recent analysis of political freedom (Shirky, 2010), economic freedom has to be accompanied by a market society economically literate enough, economically empowered enough, and interconnected enough to trade on the capital stocks issued. Western society, and increasingly the entire global society, is arguably economically literate and sufficiently interconnected to exercise economic freedom.

Economic empowerment is another matter entirely. There is no economic power without fungible capital, without ways of representing resources of all kinds, tangible and intangible, that transparently show what is available, how much of it there is, and what quality it is. A form of currency expressing the value of that capital is essential, but money is wildly insufficient to the task of determining the quality and quantity of the available capital stocks.

Today’s education, health care, human resource, and environmental quality markets are the diametric opposite of the markets in which investors, producers, and consumers are empowered. Only when dead human, social, and natural capital is brought to life in efficient markets (Fisher, 2011) will we empower ourselves with fuller degrees of creative control over our economic lives.

The crux of the economic empowerment issue is this: in the current context of inefficient intangibles markets, everyone is personally commodified. Everything that makes me valuable to an employer or investor or customer, my skills, motivations, health, and trustworthiness, is unjustifiably reduced to a homogenized unit of labor. And in the social and environmental quality markets, voting our shares is cumbersome, expensive, and often ineffective because of the immense amount of work that has to be done to defend each particular living manifestation of the value we want to protect.

Concentrated economic power is exercised in the mass markets of dead, socialized intangible assets in ways that we are taught to think of as impersonal and indifferent to each of us as individuals, but which is actually experienced by us as intensely personal.

So what is the difference between being treated personally as a commodity and being treated impersonally as a commodity? This is the same as asking what it would mean to be empowered economically with creative control over the stocks of human, social, and natural capital that are rightfully our private property. This difference is the difference between dead and living capital (Fisher, 2002, 2011).

Freedom of economic communication, realized in the trade of privately owned stocks of any form of capital, ought to be the highest priority in the way we think about the infrastructure of a sustainable and socially responsible economy. For maximum efficiency, that freedom requires a common meaningful and rigorous quantitative language enabling determinations of what exactly is for sale, and its quality, quantity, and unit price. As I have ad nauseum repeated in this blog, measurement based in scientifically calibrated instrumentation traceable to consensus standards is absolutely essential to meeting this need.

Coming in at a very close second to the highest priority is securing the ability to trade. A strong market society, where people can exercise the right to control their own private property—their personal stocks of human, social, and natural capital—in highly efficient markets, is more important than policies, regulations, and five-year plans dictating how masses of supposedly homogenous labor, social, and environmental commodities are priced and managed.

So instead of reacting to the downside of the business cycle with a socialistic safety net, how might a capitalistic one prove more humane, moral, and economically profitable? Instead of guaranteeing a limited amount of unemployment insurance funded through taxes, what we should have are requirements for minimum investments in social capital. Instead of employment in the usual sense of the term, with its implications of hiring and firing, we should have an open market for fungible human capital, in which everyone can track the price of their stock, attract and make new investments, take profits and income, upgrade the quality and/or quantity of their stock, etc.

In this context, instead of receiving unemployment compensation, workers not currently engaged in remunerated use of their skills would cash in some of their accumulated stock of social capital. The cost of social capital would go up in periods of high demand, as during the recent economic downturns caused by betrayals of trust and commitment (which are, in effect, involuntary expenditures of social capital). Conversely, the cost of human capital would also fluctuate with supply and demand, with the profits (currently referred to as wages) turned by individual workers rising and falling with the price of their stocks. These ups and downs, being absorbed by everyone in proportion to their investments, would reduce the distorted proportions we see today in the shares of the rewards and punishments allotted.

Though no one would have a guaranteed wage, everyone would have the opportunity to manage their capital to the fullest, by upgrading it, keeping it current, and selling it to the highest bidder. Ebbing and flowing tides would more truly lift and drop all boats together, with the drops backed up with the social capital markets’ tangible reassurance that we are all in this together. This kind of a social capitalism transforms the supposedly impersonal but actually highly personal indifference of flows in human capital into a more fully impersonal indifference in which individuals have the potential to maximize the realization of their personal goals.

What we need is to create a visible alternative to the bankrupt economic system in a kind of reverse shock doctrine. Eleanor Roosevelt often said that the thing we are most afraid of is the thing we most need to confront if we are to grow. The more we struggle against what we fear, the further we are carried away from what we want. Only when we relax into the binding constraints do we find them loosened. Only when we channel overwhelming force against itself or in a productive direction can we withstand attack. When we find the courage to go where the wild things are and look the monsters in the eye will we have the opportunity to see if their fearful aspect is transformed to playfulness. What is left is often a more mundane set of challenges, the residuals of a developmental transition to a new level of hierarchical complexity.

And this is the case with the moral implications of the concept of human capital. Treating individuals as fungible commodities is a way that some use to protect themselves from feeling like monsters and from being discarded as well. Those who find themselves removed from the satisfactions of working life can blame the shortsightedness of their former colleagues, or the ugliness of the unfeeling system. But neither defensive nor offensive rationalizations do anything to address the actual problem, and the problem has nothing to do with the morality or the immorality of the concept of human capital.

The problem is the problem. That is, the way we approach and define the problem delimits the sphere of the creative options we have for solving it. As Henry Ford is supposed to have said, whether you think you can or you think you cannot, you’re probably right. It is up to us to decide whether we can create an economic system that justifies its reductions and actually lives up to its billing as impersonal and unbiased, or if we cannot. Either way, we’ll have to accept and live with the consequences.

References

DeSoto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2011, Spring). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), in press.

Hayek, F. A. (1948). Individualism and economic order. Chicago: University of Chicago Press.

Hayek, F. A. (1988). The fatal conceit: The errors of socialism (W. W. Bartley, III, Ed.) The Collected Works of F. A. Hayek. Chicago: University of Chicago Press.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Shirky, C. (2010, December 20). The political power of social media: Technology, the public sphere, and political change. Foreign Affairs, 90(1), http://www.foreignaffairs.com/articles/67038/clay-shirky/the-political-power-of-social-media.

Creative Commons License
LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

A Simple Example of How Better Measurement Creates New Market Efficiencies, Reduces Transaction Costs, and Enables the Pricing of Intangible Assets

March 4, 2011

One of the ironies of life is that we often overlook the obvious in favor of the obscure. And so one hears of huge resources poured into finding and capitalizing on opportunities that provide infinitesimally small returns, while other opportunities—with equally certain odds of success but far more profitable returns—are completely neglected.

The National Institute for Standards and Technology (NIST) reports returns on investment ranging from 32% to over 400% in 32 metrological improvements made in semiconductors, construction, automation, computers, materials, manufacturing, chemicals, photonics, communications and pharmaceuticals (NIST, 2009). Previous posts in this blog offer more information on the economic value of metrology. The point is that the returns obtained from improvements in the measurement of tangible assets will likely also be achieved in the measurement of intangible assets.

How? With a little bit of imagination, each stage in the development of increasingly meaningful, efficient, and useful measures described in this previous post can be seen as implying a significant return on investment. As those returns are sought, investors will coordinate and align different technologies and resources relative to a roadmap of how these stages are likely to unfold in the future, as described in this previous post. The basic concepts of how efficient and meaningful measurement reduces transaction costs and market frictions, and how it brings capital to life, are explained and documented in my publications (Fisher, 2002-2011), but what would a concrete example of the new value created look like?

The examples I have in mind hinge on the difference between counting and measuring. Counting is a natural and obvious thing to do when we need some indication of how much of something there is. But counting is not measuring (Cooper & Humphry, 2010; Wright, 1989, 1992, 1993, 1999). This is not some minor academic distinction of no practical use or consequence. It is rather the source of the vast majority of the problems we have in comparing outcome and performance measures.

Imagine how things would be if we couldn’t weigh fruit in a grocery store, and all we could do was count pieces. We can tell when eight small oranges possess less overall mass of fruit than four large ones by weighing them; the eight small oranges might weigh .75 kilograms (about 1.6 pounds) while the four large ones come in at 1.0 kilo (2.2 pounds). If oranges were sold by count instead of weight, perceptive traders would buy small oranges and make more money selling them than they could if they bought large ones.

But we can’t currently arrive so easily at the comparisons we need when we’re buying and selling intangible assets, like those produced as the outcomes of educational, health care, or other services. So I want to walk through a couple of very down-to-earth examples to bring the point home. Today we’ll focus on the simplest version of the story, and tomorrow we’ll take up a little more complicated version, dealing with the counts, percentages, and scores used in balanced scorecard and dashboard metrics of various kinds.

What if you score eight on one reading test and I score four on a different reading test? Who has more reading ability? In the same way that we might be able to tell just by looking that eight small oranges are likely to have less actual orange fruit than four big ones, we might also be able to tell just by looking that eight easy (short, common) words can likely be read correctly with less reading ability than four difficult (long, rare) words can be.

So let’s analyze the difference between buying oranges and buying reading ability. We’ll set up three scenarios for buying reading ability. In all three, we’ll imagine we’re comparing how we buy oranges with the way we would have to go about buying reading ability today if teachers were paid for the gains made on the tests they administer at the beginning and end of the school year.

In the first scenario, the teachers make up their own tests. In the second, the teachers each use a different standardized test. In the third, each teacher uses a computer program that draws questions from the same online bank of precalibrated items to construct a unique test custom tailored to each student. Reading ability scenario one is likely the most commonly found in real life. Scenario three is the rarest, but nonetheless describes a situation that has been available to millions of students in the U.S., Australia, and elsewhere for several years. Scenarios one, two and three correspond with developmental levels one, three, and five described in a previous blog entry.

Buying Oranges

When you go into one grocery store and I go into another, we don’t have any oranges with us. When we leave, I have eight and you have four. I have twice as many oranges as you, but yours weigh a kilo, about a third more than mine (.75 kilos).

When we paid for the oranges, the transaction was finished in a few seconds. Neither one of us experienced any confusion, annoyance, or inconvenience in relation to the quality of information we had on the amount of orange fruits we were buying. I did not, however, pay twice as much as you did. In fact, you paid more for yours than I did for mine, in direct proportion to the difference in the measured amounts.

No negotiations were necessary to consummate the transactions, and there was no need for special inquiries about how much orange we were buying. We knew from experience in this and other stores that the prices we paid were comparable with those offered in other times and places. Our information was cheap, as it was printed on the bag of oranges or could be read off a scale, and it was very high quality, as the measures were directly comparable with measures from any other scale in any other store. So, in buying oranges, the impact of information quality on the overall cost of the transaction was so inexpensive as to be negligible.

Buying Reading Ability (Scenario 1)

So now you and I go through third grade as eight year olds. You’re in one school and I’m in another. We have different teachers. Each teacher makes up his or her own reading tests. When we started the school year, we each took a reading test (different ones), and we took another (again, different ones) as we ended the school year.

For each test, your teacher counted up your correct answers and divided by the total number of questions; so did mine. You got 72% correct on the first one, and 94% correct on the last one. I got 83% correct on the first one, and 86% correct on the last one. Your score went up 22%, much more than the 3% mine went up. But did you learn more? It is impossible to tell. What if both of your tests were easier—not just for you or for me but for everyone—than both of mine? What if my second test was a lot harder than my first one? On the other hand, what if your tests were harder than mine? Perhaps you did even better than your scores seem to indicate.

We’ll just exclude from consideration other factors that might come to bear, such as whether your tests were significantly longer or shorter than mine, or if one of us ran out of time and did not answer a lot of questions.

If our parents had to pay the reading teacher at the end of the school year for the gains that were made, how would they tell what they were getting for their money? What if your teacher gave a hard test at the start of the year and an easy one at the end of the year so that you’d have a big gain and your parents would have to pay more? What if my teacher gave an easy test at the start of the year and a hard one at the end, so that a really high price could be put on very small gains? If our parents were to compare their experiences in buying our improved reading ability, they would have a lot of questions about how much improvement was actually obtained. They would be confused and annoyed at how inconvenient the scores are, because they are difficult, if not impossible, to compare. A lot of time and effort might be invested in examining the words and sentences in each of the four reading tests to try to determine how easy or hard they are in relation to each other. Or, more likely, everyone would throw their hands up and pay as little as they possibly can for outcomes they don’t understand.

Buying Reading Ability (Scenario 2)

In this scenario, we are third graders again, in different schools with different reading teachers. Now, instead of our teachers making up their own tests, our reading abilities are measured at the beginning and the end of the school year using two different standardized tests sold by competing testing companies. You’re in a private suburban school that’s part of an independent schools association. I’m in a public school along with dozens of others in an urban school district.

For each test, our parents received a report in the mail showing our scores. As before, we know how many questions we each answered correctly, and, unlike before, we don’t know which particular questions we got right or wrong. Finally, we don’t know how easy or hard your tests were relative to mine, but we know that the two tests you took were equated, and so were the two I took. That means your tests will show how much reading ability you gained, and so will mine.

We have one new bit of information we didn’t have before, and that’s a percentile score. Now we know that at the beginning of the year, with a percentile ranking of 72, you performed better than 72% of the other private school third graders taking this test, and at the end of the year you performed better than 76% of them. In contrast, I had percentiles of 84 and 89.

The question we have to ask now is if our parents are going to pay for the percentile gain, or for the actual gain in reading ability. You and I each learned more than our peers did on average, since our percentile scores went up, but this would not work out as a satisfactory way to pay teachers. Averages being averages, if you and I learned more and faster, someone else learned less and slower, so that, in the end, it all balances out. Are we to have teachers paying parents when their children learn less, simply redistributing money in a zero sum game?

And so, additional individualized reports are sent to our parents by the testing companies. Your tests are equated with each other, and they measure in a comparable unit that ranges from 120 to 480. You had a starting score of 235 and finished the year with a score of 420, for a gain of 185.

The tests I took are comparable and measure in the same unit, too, but not the same unit as your tests measure in. Scores on my tests range from 400 to 1200. I started the year with a score of 790, and finished at 1080, for a gain of 290.

Now the confusion in the first scenario is overcome, in part. Our parents can see that we each made real gains in reading ability. The difficulty levels of the two tests you took are the same, as are the difficulties of the two tests I took. But our parents still don’t know what to pay the teacher because they can’t tell if you or I learned more. You had lower percentiles and test scores than I did, but you are being compared with what is likely a higher scoring group of suburban and higher socioeconomic status students than the urban group of disadvantaged students I’m compared against. And your scores aren’t comparable with mine, so you might have started and finished with more reading ability than I did, or maybe I had more than you. There isn’t enough information here to tell.

So, again, the information that is provided is insufficient to the task of settling on a reasonable price for the outcomes obtained. Our parents will again be annoyed and confused by the low quality information that makes it impossible to know what to pay the teacher.

Buying Reading Ability (Scenario 3)

In the third scenario, we are still third graders in different schools with different reading teachers. This time our reading abilities are measured by tests that are completely unique. Every student has a test custom tailored to their particular ability. Unlike the tests in the first and second scenarios, however, now all of the tests have been constructed carefully on the basis of extensive data analysis and experimental tests. Different testing companies are providing the service, but they have gone to the trouble to work together to create consensus standards defining the unit of measurement for any and all reading test items.

For each test, our parents received a report in the mail showing our measures. As before, we know how many questions we each answered correctly. Now, though we don’t know which particular questions we got right or wrong, we can see typical items ordered by difficulty lined up in a way that shows us what kind of items we got wrong, and which kind we got right. And now we also know your tests were equated relative to mine, so we can compare how much reading ability you gained relative to how much I gained. Now our parents can confidently determine how much they should pay the teacher, at least in proportion to their children’s relative measures. If our measured gains are equal, the same payment can be made. If one of us obtained more value, then proportionately more should be paid.

In this third scenario, we have a situation directly analogous to buying oranges. You have a measured amount of increased reading ability that is expressed in the same unit as my gain in reading ability, just as the weights of the oranges are comparable. Further, your test items were not identical with mine, and so the difficulties of the items we took surely differed, just as the sizes of the oranges we bought did.

This third scenario could be made yet more efficient by removing the need for creating and maintaining a calibrated item bank, as described by Stenner and Stone (2003) and in the sixth developmental level in a prior blog post here. Also, additional efficiencies could be gained by unifying the interpretation of the reading ability measures, so that progress through high school can be tracked with respect to the reading demands of adult life (Williamson, 2008).

Comparison of the Purchasing Experiences

In contrast with the grocery store experience, paying for increased reading ability in the first scenario is fraught with low quality information that greatly increases the cost of the transactions. The information is of such low quality that, of course, hardly anyone bothers to go to the trouble to try to decipher it. Too much cost is associated with the effort to make it worthwhile. So, no one knows how much gain in reading ability is obtained, or what a unit gain might cost.

When a school district or educational researchers mount studies to try to find out what it costs to improve reading ability in third graders in some standardized unit, they find so much unexplained variation in the costs that they, too, raise more questions than answers.

In grocery stores and other markets, we don’t place the cost of making the value comparison on the consumer or the merchant. Instead, society as a whole picks up the cost by funding the creation and maintenance of consensus standard metrics. Until we take up the task of doing the same thing for intangible assets, we cannot expect human, social, and natural capital markets to obtain the efficiencies we take for granted in markets for tangible assets and property.

References

Cooper, G., & Humphry, S. M. (2010). The ontological distinction between units and entities. Synthese, pp. DOI 10.1007/s11229-010-9832-1.

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [http://www.rasch.org/rmt/rmt154j.htm].

Fisher, W. P., Jr. (2003). Measurement and communities of inquiry. Rasch Measurement Transactions, 17(3), 936-8 [http://www.rasch.org/rmt/rmt173.pdf].

Fisher, W. P., Jr. (2004, October). Meaning and method in the social sciences. Human Studies: A Journal for Philosophy and the Social Sciences, 27(4), 429-54.

Fisher, W. P., Jr. (2005). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-9 [http://www.livingcapitalmetrics.com/images/FisherJAM05.pdf].

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287.

Fisher, W. P.. Jr. (2009b). NIST Critical national need idea White Paper: Metrological infrastructure for human, social, and natural capital (Tech. Rep., http://www.livingcapitalmetrics.com/images/FisherNISTWhitePaper2.pdf). New Orleans: LivingCapitalMetrics.com.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), in press.

NIST. (2009, 20 July). Outputs and outcomes of NIST laboratory research. Available: http://www.nist.gov/director/planning/studies.cfm (Accessed 1 March 2011).

Stenner, A. J., & Stone, M. (2003). Item specification vs. item banking. Rasch Measurement Transactions, 17(3), 929-30 [http://www.rasch.org/rmt/rmt173a.htm].

Williamson, G. L. (2008). A text readability continuum for postsecondary readiness. Journal of Advanced Academics, 19(4), 602-632.

Wright, B. D. (1989). Rasch model from counting right answers: Raw scores as sufficient statistics. Rasch Measurement Transactions, 3(2), 62 [http://www.rasch.org/rmt/rmt32e.htm].

Wright, B. D. (1992, Summer). Scores are not measures. Rasch Measurement Transactions, 6(1), 208 [http://www.rasch.org/rmt/rmt61n.htm].

Wright, B. D. (1993). Thinking with raw scores. Rasch Measurement Transactions, 7(2), 299-300 [http://www.rasch.org/rmt/rmt72r.htm].

Wright, B. D. (1999). Common sense for measurement. Rasch Measurement Transactions, 13(3), 704-5  [http://www.rasch.org/rmt/rmt133h.htm].

Creative Commons License
LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

 

One of the ironies of life is that we often overlook the obvious in favor of the obscure. And so one hears of huge resources poured into finding and capitalizing on opportunities that provide infinitesimally small returns, while other opportunities—with equally certain odds of success but far more profitable returns—are completely neglected.

The National Institute for Standards and Technology (NIST) reports returns on investment ranging from 32% to over 400% in 32 metrological improvements made in semiconductors, construction, automation, computers, materials, manufacturing, chemicals, photonics, communications and pharmaceuticals (NIST, 2009). Previous posts in this blog offer more information on the economic value of metrology. The point is that the returns obtained from improvements in the measurement of tangible assets will likely also be achieved in the measurement of intangible assets.

How? With a little bit of imagination, each stage in the development of increasingly meaningful, efficient, and useful measures described in this previous post can be seen as implying a significant return on investment. As those returns are sought, investors will coordinate and align different technologies and resources relative to a roadmap of how these stages are likely to unfold in the future, as described in this previous post. But what would a concrete example of the new value created look like?

The examples I have in mind hinge on the difference between counting and measuring. Counting is a natural and obvious thing to do when we need some indication of how much of something there is. But counting is not measuring (Cooper & Humphry, 2010; Wright, 1989, 1992, 1993, 1999). This is not some minor academic distinction of no practical use or consequence. It is rather the source of the vast majority of the problems we have in comparing outcome and performance measures.

Imagine how things would be if we couldn’t weigh fruit in a grocery store, and all we could do was count pieces. We can tell when eight small oranges possess less overall mass of fruit than four large ones by weighing them; the eight small oranges might weigh .75 kilograms (about 1.6 pounds) while the four large ones come in at 1.0 kilo (2.2 pounds). If oranges were sold by count instead of weight, perceptive traders would buy small oranges and make more money selling them than they could if they bought large ones.

But we can’t currently arrive so easily at the comparisons we need when we’re buying and selling intangible assets, like those produced as the outcomes of educational, health care, or other services. So I want to walk through a couple of very down-to-earth examples to bring the point home. Today we’ll focus on the simplest version of the story, and tomorrow we’ll take up a little more complicated version, dealing with the counts, percentages, and scores used in balanced scorecard and dashboard metrics of various kinds.

What if you score eight on one reading test and I score four on a different reading test? Who has more reading ability? In the same way that we might be able to tell just by looking that eight small oranges are likely to have less actual orange fruit than four big ones, we might also be able to tell just by looking that eight easy (short, common) words can likely be read correctly with less reading ability than four difficult (long, rare) words can be.

So let’s analyze the difference between buying oranges and buying reading ability. We’ll set up three scenarios for buying reading ability. In all three, we’ll imagine we’re comparing how we buy oranges with the way we would have to go about buying reading ability today if teachers were paid for the gains made on the tests they administer at the beginning and end of the school year.

In the first scenario, the teachers make up their own tests. In the second, the teachers each use a different standardized test. In the third, each teacher uses a computer program that draws questions from the same online bank of precalibrated items to construct a unique test custom tailored to each student. Reading ability scenario one is likely the most commonly found in real life. Scenario three is the rarest, but nonetheless describes a situation that has been available to millions of students in the U.S., Australia, and elsewhere for several years. Scenarios one, two and three correspond with developmental levels one, three, and five described in a previous blog entry.

Buying Oranges

When you go into one grocery store and I go into another, we don’t have any oranges with us. When we leave, I have eight and you have four. I have twice as many oranges as you, but yours weigh a kilo, about a third more than mine (.75 kilos).

When we paid for the oranges, the transaction was finished in a few seconds. Neither one of us experienced any confusion, annoyance, or inconvenience in relation to the quality of information we had on the amount of orange fruits we were buying. I did not, however, pay twice as much as you did. In fact, you paid more for yours than I did for mine, in direct proportion to the difference in the measured amounts.

No negotiations were necessary to consummate the transactions, and there was no need for special inquiries about how much orange we were buying. We knew from experience in this and other stores that the prices we paid were comparable with those offered in other times and places. Our information was cheap, as it was printed on the bag of oranges or could be read off a scale, and it was very high quality, as the measures were directly comparable with measures from any other scale in any other store. So, in buying oranges, the impact of information quality on the overall cost of the transaction was so inexpensive as to be negligible.

Buying Reading Ability (Scenario 1)

So now you and I go through third grade as eight year olds. You’re in one school and I’m in another. We have different teachers. Each teacher makes up his or her own reading tests. When we started the school year, we each took a reading test (different ones), and we took another (again, different ones) as we ended the school year.

For each test, your teacher counted up your correct answers and divided by the total number of questions; so did mine. You got 72% correct on the first one, and 94% correct on the last one. I got 83% correct on the first one, and 86% correct on the last one. Your score went up 22%, much more than the 3% mine went up. But did you learn more? It is impossible to tell. What if both of your tests were easier—not just for you or for me but for everyone—than both of mine? What if my second test was a lot harder than my first one? On the other hand, what if your tests were harder than mine? Perhaps you did even better than your scores seem to indicate.

We’ll just exclude from consideration other factors that might come to bear, such as whether your tests were significantly longer or shorter than mine, or if one of us ran out of time and did not answer a lot of questions.

If our parents had to pay the reading teacher at the end of the school year for the gains that were made, how would they tell what they were getting for their money? What if your teacher gave a hard test at the start of the year and an easy one at the end of the year so that you’d have a big gain and your parents would have to pay more? What if my teacher gave an easy test at the start of the year and a hard one at the end, so that a really high price could be put on very small gains? If our parents were to compare their experiences in buying our improved reading ability, they would have a lot of questions about how much improvement was actually obtained. They would be confused and annoyed at how inconvenient the scores are, because they are difficult, if not impossible, to compare. A lot of time and effort might be invested in examining the words and sentences in each of the four reading tests to try to determine how easy or hard they are in relation to each other. Or, more likely, everyone would throw their hands up and pay as little as they possibly can for outcomes they don’t understand.

Buying Reading Ability (Scenario 2)

In this scenario, we are third graders again, in different schools with different reading teachers. Now, instead of our teachers making up their own tests, our reading abilities are measured at the beginning and the end of the school year using two different standardized tests sold by competing testing companies. You’re in a private suburban school that’s part of an independent schools association. I’m in a public school along with dozens of others in an urban school district.

For each test, our parents received a report in the mail showing our scores. As before, we know how many questions we each answered correctly, and, as before, we don’t know which particular questions we got right or wrong. Finally, we don’t know how easy or hard your tests were relative to mine, but we know that the two tests you took were equated, and so were the two I took. That means your tests will show how much reading ability you gained, and so will mine.

But we have one new bit of information we didn’t have before, and that’s a percentile score. Now we know that at the beginning of the year, with a percentile ranking of 72, you performed better than 72% of the other private school third graders taking this test, and at the end of the year you performed better than 76% of them. In contrast, I had percentiles of 84 and 89.

The question we have to ask now is if our parents are going to pay for the percentile gain, or for the actual gain in reading ability. You and I each learned more than our peers did on average, since our percentile scores went up, but this would not work out as a satisfactory way to pay teachers. Averages being averages, if you and I learned more and faster, someone else learned less and slower, so that, in the end, it all balances out. Are we to have teachers paying parents when their children learn less, simply redistributing money in a zero sum game?

And so, additional individualized reports are sent to our parents by the testing companies. Your tests are equated with each other, so they measure in a comparable unit that ranges from 120 to 480. You had a starting score of 235 and finished the year with a score of 420, for a gain of 185.

The tests I took are comparable and measure in the same unit, too, but not the same unit as your tests measure in. Scores on my tests range from 400 to 1200. I started the year with a score of 790, and finished at 1080, for a gain of 290.

Now the confusion in the first scenario is overcome, in part. Our parents can see that we each made real gains in reading ability. The difficulty levels of the two tests you took are the same, as are the difficulties of the two tests I took. But our parents still don’t know what to pay the teacher because they can’t tell if you or I learned more. You had lower percentiles and test scores than I did, but you are being compared with what is likely a higher scoring group of suburban and higher socioeconomic status students than the urban group of disadvantaged students I’m compared against. And your scores aren’t comparable with mine, so you might have started and finished with more reading ability than I did, or maybe I had more than you. There isn’t enough information here to tell.

So, again, the information that is provided is insufficient to the task of settling on a reasonable price for the outcomes obtained. Our parents will again be annoyed and confused by the low quality information that makes it impossible to know what to pay the teacher.

Buying Reading Ability (Scenario 3)

In the third scenario, we are still third graders in different schools with different reading teachers. This time our reading abilities are measured by tests that are completely unique. Every student has a test custom tailored to their particular ability. Unlike the tests in the first and second scenarios, however, now all of the tests have been constructed carefully on the basis of extensive data analysis and experimental tests. Different testing companies are providing the service, but they have gone to the trouble to work together to create consensus standards defining the unit of measurement for any and all reading test items.

For each test, our parents received a report in the mail showing our measures. As before, we know how many questions we each answered correctly. Now, though we don’t know which particular questions we got right or wrong, we can see typical items ordered by difficulty lined up in a way that shows us what kind of items we got wrong, and which kind we got right. And now we also know your tests were equated relative to mine, so we can compare how much reading ability you gained relative to how much I gained. Now our parents can confidently determine how much they should pay the teacher, at least in proportion to their children’s relative measures. If our measured gains are equal, the same payment can be made. If one of us obtained more value, then proportionately more should be paid.

In this third scenario, we have a situation directly analogous to buying oranges. You have a measured amount of increased reading ability that is expressed in the same unit as my gain in reading ability, just as the weights of the oranges are comparable. Further, your test items were not identical with mine, and so the difficulties of the items we took surely differed, just as the sizes of the oranges we bought did.

This third scenario could be made yet more efficient by removing the need for creating and maintaining a calibrated item bank, as described by Stenner and Stone (2003) and in the sixth developmental level in a prior blog post here. Also, additional efficiencies could be gained by unifying the interpretation of the reading ability measures, so that progress through high school can be tracked with respect to the reading demands of adult life (Williamson, 2008).

Comparison of the Purchasing Experiences

In contrast with the grocery store experience, paying for increased reading ability in the first scenario is fraught with low quality information that greatly increases the cost of the transactions. The information is of such low quality that, of course, hardly anyone bothers to go to the trouble to try to decipher it. Too much cost is associated with the effort to make it worthwhile. So, no one knows how much gain in reading ability is obtained, or what a unit gain might cost.

When a school district or educational researchers mount studies to try to find out what it costs to improve reading ability in third graders in some standardized unit, they find so much unexplained variation in the costs that they, too, raise more questions than answers.

But we don’t place the cost of making the value comparison on the consumer or the merchant in the grocery store. Instead, society as a whole picks up the cost by funding the creation and maintenance of consensus standard metrics. Until we take up the task of doing the same thing for intangible assets, we cannot expect human, social, and natural capital markets to obtain the efficiencies we take for granted in markets for tangible assets and property.

References

Cooper, G., & Humphry, S. M. (2010). The ontological distinction between units and entities. Synthese, pp. DOI 10.1007/s11229-010-9832-1.

NIST. (2009, 20 July). Outputs and outcomes of NIST laboratory research. Available: http://www.nist.gov/director/planning/studies.cfm (Accessed 1 March 2011).

Stenner, A. J., & Stone, M. (2003). Item specification vs. item banking. Rasch Measurement Transactions, 17(3), 929-30 [http://www.rasch.org/rmt/rmt173a.htm].

Williamson, G. L. (2008). A text readability continuum for postsecondary readiness. Journal of Advanced Academics, 19(4), 602-632.

Wright, B. D. (1989). Rasch model from counting right answers: Raw scores as sufficient statistics. Rasch Measurement Transactions, 3(2), 62 [http://www.rasch.org/rmt/rmt32e.htm].

Wright, B. D. (1992, Summer). Scores are not measures. Rasch Measurement Transactions, 6(1), 208 [http://www.rasch.org/rmt/rmt61n.htm].

Wright, B. D. (1993). Thinking with raw scores. Rasch Measurement Transactions, 7(2), 299-300 [http://www.rasch.org/rmt/rmt72r.htm].

Wright, B. D. (1999). Common sense for measurement. Rasch Measurement Transactions, 13(3), 704-5  [http://www.rasch.org/rmt/rmt133h.htm].

Measurement, Metrology, and the Birth of Self-Organizing, Complex Adaptive Systems

February 28, 2011

On page 145 of his book, The Mathematics of Measurement: A Critical History, John Roche quotes Charles de La Condamine (1701-1774), who, in 1747, wrote:

‘It is quite evident that the diversity of weights and measures of different countries, and frequently in the same province, are a source of embarrassment in commerce, in the study of physics, in history, and even in politics itself; the unknown names of foreign measures, the laziness or difficulty in relating them to our own give rise to confusion in our ideas and leave us in ignorance of facts which could be useful to us.’

Roche (1998, p. 145) then explains what de La Condamine is driving at, saying:

“For reasons of international communication and of civic justice, for reasons of stability over time and for accuracy and reliability, the creation of exact, reproducible and well maintained international standards, especially of length and mass, became an increasing concern of the natural philosophers of the seventeenth and eighteenth centuries. This movement, cooperating with a corresponding impulse in governing circles for the reform of weights and measures for the benefit of society and trade, culminated in late eighteenth century France in the metric system. It established not only an exact, rational and international system of measuring length, area, volume and mass, but introduced a similar standard for temperature within the scientific community. It stimulated a wider concern within science to establish all scientific units with equal rigour, basing them wherever possible on the newly established metric units (and on the older exact units of time and angular measurement), because of their accuracy, stability and international availability. This process gradually brought about a profound change in the notation and interpretation of the mathematical formalism of physics: it brought about, for the first time in the history of the mathematical sciences, a true union of mathematics and measurement.”

As it was in the seventeenth and eighteenth centuries for physics, so it has also been in the twentieth and twenty-first for the psychosocial sciences. The creation of exact, reproducible and well maintained international standards is a matter of increasing concern today for the roles they will play in education, health care, the work place, business intelligence, and the economy at large.

As the economic crises persist and perhaps worsen, demand for common product definitions and for interpretable, meaningful measures of impacts and outcomes in education, health care, social services, environmental management, etc. will reach a crescendo. We need an exact, rational and international system of measuring literacy, numeracy, health, motivations, quality of life, community cohesion, and environmental quality, and we needed it fifty years ago. We need to reinvigorate and revive a wider concern across the sciences to establish all scientific units with equal rigor, and to have all measures used in research and practice based wherever possible on consensus standard metrics valued for their accuracy, stability and availability. We need to replicate in the psychosocial sciences the profound change in the notation and interpretation of the mathematical formalism of physics that occurred in the eighteenth and nineteenth centuries. We need to extend the true union of mathematics and measurement from physics to the psychosocial sciences.

Previous posts in this blog speak to the persistent invariance and objectivity exhibited by many of the constructs measured using ability tests, attitude surveys, performance assessments, etc. A question previously raised in this blog concerning the reproductive logic of living meaning deserves more attention, and can be productively explored in terms of complex adaptive functionality.

In a hierarchy of reasons why mathematically rigorous measurement is valuable, few are closer to the top of the list than facilitating the spontaneous self-organization of networks of agents and actors (Latour, 1987). The conception, gestation, birthing, and nurturing of complex adaptive systems constitute a reproductive logic for sociocultural traditions. Scientific traditions, in particular, form mature self-identities via a mutually implied subject-object relation absorbed into the flow of a dialectical give and take, just as economic systems do.

Complex adaptive systems establish the reproductive viability of their offspring and the coherence of an ecological web of meaningful relationships by means of this dialectic. Taylor (2003, pp. 166-8) describes the five moments in the formation and operation of complex adaptive systems, which must be able

  • to identify regularities and patterns in the flow of matter, energy, and information (MEI) in the environment (business, social, economic, natural, etc.);
  • to produce condensed schematic representations of these regularities so they can be identified as the same if they are repeated;
  • to form reproductively interchangeable variants of these representations;
  • to succeed reproductively by means of the accuracy and reliability of the representations’ predictions of regularities in the MEI data flow; and
  • adaptively modify and reorganize representations by means of informational feedback from the environment.

All living systems, from bacteria and viruses to plants and animals to languages and cultures, are complex adaptive systems characterized by these five features.

In the history of science, technologically-embodied measurement facilitates complex adaptive systems of various kinds. That history can be used as a basis for a meta-theoretical perspective on what measurement must look like in the social and human sciences. Each of Taylor’s five moments in the formation and operation of complex adaptive systems describes a capacity of measurement systems, in that:

  • data flow regularities are captured in initial, provisional instrument calibrations;
  • condensed local schematic representations are formed when an instrument’s calibrations are anchored at repeatedly observed, invariant values;
  • interchangeable nonlocal versions of these invariances are created by means of instrument equating, item banking, metrological networks, and selective, tailored, adaptive instrument administration;
  • measures read off inaccurate and unreliable instruments will not support successful reproduction of the data flow regularity, but accurate and reliable instruments calibrated in a shared common unit provide a reference standard metric that enhances communication and reproduces the common voice and shared identity of the research community; and
  • consistently inconsistent anomalous observations provide feedback suggesting new possibilities for as yet unrecognized data flow regularities that might be captured in new calibrations.

Measurement in the social sciences is in the process of extending this functionality into practical applications in business, education, health care, government, and elsewhere. Over the course of the last 50 years, measurement research and practice has already iterated many times through these five moments. In the coming years, a new critical mass will be reached in this process, systematically bringing about scale-of-magnitude improvements in the efficiency of intangible assets markets.

How? What does a “data flow regularity” look like? How is it condensed into a a schematic and used to calibrate an instrument? How are local schematics combined together in a pattern used to recognize new instances of themselves? More specifically, how might enterprise resource planning (ERP) software (such as SAP, Oracle, or PeopleSoft) simultaneously provide both the structure needed to support meaningful comparisons and the flexibility needed for good fit with the dynamic complexity of adaptive and generative self-organizing systems?

Prior work in this area proposes a dual-core, loosely coupled organization using ERP software to build social and intellectual capital, instead of using it as an IT solution addressing organizational inefficiencies (Lengnick-Hall, Lengnick-Hall, & Abdinnour-Helm, 2004). The adaptive and generative functionality (Stenner & Stone, 2003) provided by probabilistic measurement models (Rasch, 1960; Andrich, 2002, 2004; Bond & Fox, 2007; Wilson, 2005; Wright, 1977, 1999) makes it possible to model intra- and inter-organizational interoperability (Weichhart, Feiner, & Stary, 2010) at the same time that social and intellectual capital resources are augmented.

Actor/agent network theory has emerged from social and historical studies of the shared and competing moral, economic, political, and mathematical values disseminated by scientists and technicians in a variety of different successful and failed areas of research (Latour, 2005). The resulting sociohistorical descriptions ought be translated into a practical program for reproducing successful research programs. A metasystem for complex adaptive systems of research is implied in what Roche (1998) calls a “true union of mathematics and measurement.”

Complex adaptive systems are effectively constituted of such a union, even if, in nature, the mathematical character of the data flows and calibrations remains virtual. Probabilistic conjoint models for fundamental measurement are poised to extend this functionality into the human sciences. Though few, if any, have framed the situation in these terms, these and other questions are being explored, explicitly and implicitly, by hundreds of researchers in dozens of fields as they employ unidimensional models for measurement in their investigations.

If so, might then we be on the verge of a yet another new reading and writing of Galileo’s “book of nature,” this time restoring the “loss of meaning for life” suffered in Galileo’s “fateful omission” of the means by which nature came to be understood mathematically (Husserl, 1970)? The elements of a comprehensive, mathematical, and experimental design science of living systems appear on the verge of providing a saturated solution—or better, a nonequilbrium thermodynamic solution—to some of the infamous shortcomings of modern, Enlightenment science. The unity of science may yet be a reality, though not via the reductionist program envisioned by the positivists.

Some 50 years ago, Marshall McLuhan popularized the expression, “The medium is the message.” The special value quantitative measurement in the history of science does not stem from the mere use of number. Instruments are media on which nature, human or other, inscribes legible messages. A renewal of the true union of mathematics and measurement in the context of intangible assets will lead to a new cultural, scientific, and economic renaissance. As Thomas Kuhn (1977, p. 221) wrote,

“The full and intimate quantification of any science is a consummation devoutly to be wished. Nevertheless, it is not a consummation that can effectively be sought by measuring. As in individual development, so in the scientific group, maturity comes most surely to those who know how to wait.”

Given that we have strong indications of how full and intimate quantification consummates a true union of mathematics and measurement, the time for waiting is now past, and the time to act has come. See prior blog posts here for suggestions on an Intangible Assets Metric System, for resources on methods and research, for other philosophical ruminations, and more. This post is based on work presented at Rasch meetings several years ago (Fisher, 2006a, 2006b).

References

Andrich, D. (2002). Understanding resistance to the data-model relationship in Rasch’s paradigm: A reflection for the next generation. Journal of Applied Measurement, 3(3), 325-59.

Andrich, D. (2004, January). Controversy and the Rasch model: A characteristic of incompatible paradigms? Medical Care, 42(1), I-7–I-16.

Bond, T., & Fox, C. (2007). Applying the Rasch model: Fundamental measurement in the human sciences, 2d edition. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Fisher, W. P., Jr. (2006a, Friday, April 28). Complex adaptive functionality via measurement. Presented at the Midwest Objective Measurement Seminar, M. Lunz (Organizer), University of Illinois at Chicago.

Fisher, W. P., Jr. (2006b, June 27-9). Measurement and complex adaptive functionality. Presented at the Pacific Rim Objective Measurement Symposium, T. Bond & M. Wu (Organizers), The Hong Kong Institute of Education, Hong Kong.

Husserl, E. (1970). The crisis of European sciences and transcendental phenomenology: An introduction to phenomenological philosophy (D. Carr, Trans.). Evanston, Illinois: Northwestern University Press (Original work published 1954).

Kuhn, T. S. (1977). The function of measurement in modern physical science. In T. S. Kuhn, The essential tension: Selected studies in scientific tradition and change (pp. 178-224). Chicago: University of Chicago Press. [(Reprinted from Kuhn, T. S. (1961). Isis, 52(168), 161-193.]

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Latour, B. (2005). Reassembling the social: An introduction to actor-network-theory. (Clarendon Lectures in Management Studies). Oxford, England: Oxford University Press.

Lengnick-Hall, C. A., Lengnick-Hall, M. L., & Abdinnour-Helm, S. (2004). The role of social and intellectual capital in achieving competitive advantage through enterprise resource planning (ERP) systems. Journal of Engineering Technology Management, 21, 307-330.

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

Roche, J. (1998). The mathematics of measurement: A critical history. London: The Athlone Press.

Stenner, A. J., & Stone, M. (2003). Item specification vs. item banking. Rasch Measurement Transactions, 17(3), 929-30 [http://www.rasch.org/rmt/rmt173a.htm].

Taylor, M. C. (2003). The moment of complexity: Emerging network culture. Chicago: University of Chicago Press.

Weichhart, G., Feiner, T., & Stary, C. (2010). Implementing organisational interoperability–The SUddEN approach. Computers in Industry, 61, 152-160.

Wilson, M. (2005). Constructing measures: An item response modeling approach. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14(2), 97-116 [http://www.rasch.org/memo42.htm].

Wright, B. D. (1997, Winter). A history of social science measurement. Educational Measurement: Issues and Practice, 16(4), 33-45, 52 [http://www.rasch.org/memo62.htm].

Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every educator and psychologist should know (pp. 65-104 [http://www.rasch.org/memo64.htm]). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Stages in the Development of Meaningful, Efficient, and Useful Measures

February 21, 2011

In all learning, we use what we already know as a means of identifying what we do not yet know. When someone can read a written language, knows an alphabet and has a vocabulary, understands grammar and syntax, then that knowledge can be used to learn about the world. Then, knowing what birds are, for instance, one might learn about different kinds of birds or the typical behaviors of one bird species.

And so with measurement, we start from where we find ourselves, as with anything else. There is no need or possibility for everyone to master all the technical details of every different area of life that’s important. But it is essential that we know what is technically possible, so that we can seek out and find the tools that help us achieve our goals. We can’t get what we can’t or don’t ask for. In the domain of measurement, it seems that hardly anyone is looking for what’s actually readily available.

So it seems pertinent to offer a description of a continuum of increasingly meaningful, efficient and useful ways of measuring. Previous considerations of the problem have offered different categorizations for the transformations characterizing development on this continuum. Stenner and Horabin (1992) distinguish between 1) impressionistic and qualitative, nominal gradations found in the earliest conceptualizations of temperature, 2) local, data-based quantitative measures of temperature, and 3) generalized, universally uniform, theory-based quantitative measures of temperature.

Theory-based temperature measurement is prized for the way that thermodynamic theory enables the calibration of individual thermometers with no need for testing each one in empirical studies of its performance. As Lewin (1951, p. 169) put it, “There is nothing so practical as a good theory.” Thus we have electromagnetic theory making it possible to know the conduction and resistance characteristics of electrical cable from the properties of the metal alloys and insulators used, with no need to test more than a small fraction of that cable as a quality check.

Theory makes it possible to know in advance what the results of such tests would be with enough precision to greatly reduce the burden and expenses of instrument calibration. There likely would be no electrical industry at all if the properties of every centimeter of cable and every appliance had to be experimentally tested. This principle has been employed in measuring human, social, and natural capital for some time, but, for a variety of reasons, it has not yet been adopted on a wide scale.

Reflecting on the history of psychosocial measurement in this context, it then becomes apparent that Stenner and Horabin’s (1992) three stages can then be further broken down. Listed below are the distinguishing features for each of six stages in the evolution of measurement systems, building on the five stages described by Stenner, Burdick, Sanford, and Burdick (2006). This progression of increasing complexity, meaning, efficiency, and utility can be used as a basis for a technology roadmap that will enable the coordination and alignment of various services and products in the domain of intangible assets, as I will take up in a forthcoming post.

Stage 1. Least meaning, utility, efficiency, and value

Purely passive, receptive

Statistics describe data: What you see is what you get

Content defines measure

Additivity, invariance, etc. not tested, so numbers do not stand for something that adds up like they do

Measurement defined statistically in terms of group-level intervariable relations

Meaning of numbers changes with questions asked and persons answering

No theory

Data must be gathered and analyzed to have results

Commercial applications are instrument-dependent

Standards based in ensuring fair methods and processes

Stage 2

Slightly less passive, receptive but still descriptively oriented

Additivity, invariance, etc. tested, so numbers might stand for something that adds up like they do

Measurement still defined statistically in terms of group-level intervariable relations

Falsification of additive hypothesis effectively derails measurement effort

Descriptive models with interaction effects accepted as viable alternatives

Typically little or no attention to theory of item hierarchy and construct definition

Empirical (data-based) calibrations only

Data must be gathered and analyzed to have results

Initial awareness of measurement theory

Commercial applications are instrument-dependent

Standards based in ensuring fair methods and processes

Stage 3

Even less purely passive & receptive, more active

Instrument still designed relative to content specifications

Additivity, invariance, etc. tested, so numbers might stand for something that adds up like they do

Falsification of additive hypothesis provokes questions as to why

Descriptive models with interaction effects not accepted as viable alternatives

Measurement defined prescriptively in terms of individual-level intravariable invariance

Significant attention to theory of item hierarchy and construct definition

Empirical calibrations only

Data has to be gathered and analyzed to have results

More significant use of measurement theory in prescribing acceptable data quality

Limited construct theory (no predictive power)

Commercial applications are instrument-dependent

Standards based in ensuring fair methods and processes

Stage 4

First stage that is more active than passive

Initial efforts to (re-)design instrument relative to construct specifications and theory

Additivity, invariance, etc. tested in thoroughly prescriptive focus on calibrating instrument

Numbers not accepted unless they stand for something that adds up like they do

Falsification of additive hypothesis provokes questions as to why and corrective action

Models with interaction effects not accepted as viable alternatives

Measurement defined prescriptively in terms of individual-level intravariable invariance

Significant attention to theory of item hierarchy and construct definition relative to instrument design

Empirical calibrations only but model prescribes data quality

Data usually has to be gathered and analyzed to have results

Point of use self-scoring forms might provide immediate measurement results to end user

Some construct theory (limited predictive power)

Some commercial applications are not instrument-dependent (as in CAT item bank implementations)

Standards based in ensuring fair methods and processes

Stage 5

Significantly active approach to measurement

Item hierarchy translated into construct theory

Construct specification equation predicts item difficulties

Theory-predicted (not empirical) calibrations used in applications

Item banks superseded by single-use items created on the fly

Calibrations checked against empirical results but data gathering and analysis not necessary

Point of use self-scoring forms or computer apps provide immediate measurement results to end user

Used routinely in commercial applications

Awareness that standards might be based in metrological traceability to consensus standard uniform metric

Stage 6. Most meaning, utility, efficiency, and value

Most purely active approach to measurement

Item hierarchy translated into construct theory

Construct specification equation predicts item ensemble difficulties

Theory-predicted calibrations enable single-use items created from context

Checked against empirical results for quality assessment but data gathering and analysis not necessary

Point of use self-scoring forms or computer apps provide immediate measurement results to end user

Used routinely in commercial applications

Standards based in metrological traceability to consensus standard uniform metric

 

References

Lewin, K. (1951). Field theory in social science: Selected theoretical papers (D. Cartwright, Ed.). New York: Harper & Row.

Stenner, A. J., Burdick, H., Sanford, E. E., & Burdick, D. S. (2006). How accurate are Lexile text measures? Journal of Applied Measurement, 7(3), 307-22.

Stenner, A. J., & Horabin, I. (1992). Three stages of construct definition. Rasch Measurement Transactions, 6(3), 229 [http://www.rasch.org/rmt/rmt63b.htm].

Creative Commons License
LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

The Birds and the Bees of Living Meaning

November 22, 2010

or

How the New Renaissance Will be Conceived in and Midwifed from the Womb of Nature

Sex, Reproduction, and the Consumer Culture

Human sexuality is, of course, more than the sum of its biological parts. Many parents joke that human reproduction would halt and the species would go extinct were it not for the intense pleasure of sexual experience. Many social critics, for their part, have turned a jaded eye on the rampant use of sexual imagery in the consumer culture. The association of sexual prowess with anything from toothpaste to automobiles plays up an empty metaphor of immediate gratification that connotes shortchanged consumers, unfairly boosted profits, and no redeeming long term value.

We would, of course, be mistaken to make too much of a connection between the parents’ joke and the critics’ social commentary. A bit of humor can help release tension when the work of child rearing and homemaking becomes stressful, and it is unlikely that trade would come to a halt if hot dates were banned from TV commercials. Commerce, in the broad sense of the term, is an end in itself.

But perhaps there is more of a connection than is evident at first blush. Advertising is an extremely compressed form of communication. It competes with many other stimuli for fleeting seconds of attention and so has to get its message across quickly. What better, simpler, more genetically programmed message could there be than the promise of attracting a desirable mate?

This hint is the tip of the tip of an iceberg. The larger question is one that asks how the role of desire and its satisfaction in the procreation of the species might serve as a model for economic activity. Might sexual satisfaction and the resulting reproductive success be taken as a natural model for profit and the resulting economic success?

Though this model has been assumed or described to various extents in the domains of ecological, behavioral, and heterodox economics, what we might call its molecular genetics have not yet been described. At this level, the model functions as a positive-sum game, and not as the zero-sum game so often assumed in economics. Properly conceived and experienced, neither sexuality nor profit give one-sided results, with someone necessarily winning and someone else necessarily losing. Rather, in the optimal circumstances we presumably want to foster, both parties to the exchanges must get what they want and contribute to the overall product of the exchange.

In this scenario, profit has to be further defined as not mere gratification and conquest, but as long term reproductive viability and sustainability. The intensity of sexual desire and satisfaction would likely not have evolved without stakes as high as the continuity of the species. And, indeed, researchers are finding strong positive relationships between firms’ long term profitability and their relations with labor, their communities, and the natural environment. Broadly conceived, for commerce to continue, social intercourse can and ultimately must result in viable offspring situated in a supportive environment.

Living vs Dead Capital

All of this suggests that we might be onto something. But for the metaphor to work, we need to take it further. We find what we need in the language of ecological economics and natural capital, and in the distinction between economically alive and economically dead capital.

The ancient root metaphor hidden in the word “capital” derives from the Latin capitus, head. Some might locate scientific or intellectual capital in a calculating center, like the brain, but others might bring out a sense of capital as part of the natural order. The concept of capital likely emerged in early agricultural economies from a focus on head of livestock: cattle, sheep, horses, etc. We might also conjecture about an even earlier prehistorical sense of capital as naturally embodied in the herds of antelope, deer, elk, or bison that migratory hunters pursued. In both cases, given grazing and water resources supplied by nature, herds replenished themselves with the passing of the seasons, giving birth to new life of their own accord.

There is a sense then in which plant and animal life profits enough from naturally available resources to sustain itself. Though the occurrence of population booms and busts still parallels economic cycles, hunters, fishers, and farmers can be imagined as profiting from managing naturally self-restoring resources within the constraints of a sustainable ecology.

Living capital and the sustenance of ongoing ecologically sound profitability are not restricted, however, to forms of capital stock that walk, crawl, swim, or fly. De Soto (2000) makes a distinction between dead and living capital that explains why capitalism thrives in some countries, but has not yet in others. De Soto points out that the difference between successful and failing capitalist countries lies in the status of what he calls transferable representations within networks of legal and financial institutions. Transferable representations are nothing but the legally recognized and financially fungible titles and deeds that make it possible for the wealth locked up in land, buildings, and equipment to be made exchangeable for other forms of wealth. Titles, deeds, and the infrastructure they function within are, then, what comprise the difference between dead and living capital.

In North America, Europe, Australia, and Japan, property can be divided into shares and sold, or accumulated across properties into an expression of total wealth and leveraged as collateral for further investment, all with no need to modify the property itself in any way. De Soto’s point is that this is often not so in the Third World and former communist countries, where it commonly takes more than 10 years of full time work to obtain legal title, and then similar degrees of effort to maintain it. The process requires so much labor that few have the endurance or resources to complete it. They then must deny themselves the benefits of having an address, and cannot receive mail, electrical service, or take out a mortgage. The economy is then encumbered by the dead weight of the inefficiencies and frictions of frozen capital markets.

In the same way that the mass migration of settlers to the American West forced the resolution of conflicting property claims in the nineteenth century via the Preemption Act, so, too, are the contemporary mass migrations of rural people to megacities around the globe forcing the creation of a new way of legitimating property ownership. DeSoto’s research shows that Third World and former communist countries harbor trillions of dollars of unleverageable dead capital. Individual countries have more wealth tied up as dead capital locked in their impoverished citizens’ homes than in their entire stock markets and GDPs.

So dead capital can be clearly and decisively distinguished from living capital. Living capital is represented by a title or deed legally sanctioned by society as a generally accepted demonstration of ownership. Capital is dead, or, better, not yet brought to life, when its general value (any value it may have beyond its utilitarian function) cannot be represented so as to be leveragable or transferable across time, space, applications, enterprises, etc.

An essential point is this: Human, social, and natural forms of capital are dead in the same way that Third World property is dead capital. We lack a means of representing the value of these forms of capital that is transferable across individuals and contexts. The sense of scientific capital as mobile, additive, and divisible, and as deployed via networks of metrological (measurement science) laboratories, is especially helpful here, as it provides a root definition of what capital is. The geometry of the geodetic survey information incorporated into titles and deeds provides a fundamental insight into capitalism and living capital. But an even better understanding can be found by looking more deeply into the metaphor equating sexual and economic success.

The Birds and the Bees

We all learn as children where babies come from. Spontaneous questions from curious kids can be simultaneously intimidating and hilarious. Discovering that we each came into existence at a certain point in time raises many questions. Children are usually interested, however, in a short answer to a specific question. They go about their processes of creating meaningful stories about the world slowly, bit by bit. Contrary to many parents’ fears, children are less interested in the big picture than they are in knowing something immediately relevant.

Today we are engaged in a similar process that involves both self-discovery and its extension into a model of the world. In the last 100 years, we have endured one crisis of alienation, war, and terrorism after another. So many different stresses are pulling life in so many different directions that it has become difficult to fit our lives into meaningful stories about the world. Anxiety about our roles and places relative to one another has led many of us to be either increasingly lax or increasingly rigid about where we stand. Being simultaneously intelligent and compassionate is more difficult than ever.

But perhaps we know more than we are aware of. Perhaps it would help for us to consider more closely where we as a people, with our modern, global culture, come from. Where did the ideas that shape our world come from? Where do new ideas in general come from? What happens when an idea comes alive with meaning and spreads with such rapidity that it seems to spring forth fully formed in many widely distant places? How does a meme become viral and spread like an epidemic? Questions like these have often been raised in recent years. It seems to me, though, that explorations of them to date have not focused as closely as they could have on what is most important.

For when we understand the reproductive biology of living meaning, and when we see how different species of conceptual life interrelate in larger ecologies, then we will be in the position we need to be in to newly harmonize nature and culture, male and female, black and white, capitalism and socialism, north and south, and east and west.

What is most important about knowing where modern life comes from? What is most important is often that which is most obvious, and the most taken for granted. Given the question, it is interesting that rich metaphors of biological reproduction are everywhere in our thinking about ideas and meaning. Ideas are conceived, for instance, and verbs are conjugated.

These metaphors are not just poetic, emotionally soothing, or apt in a locally specific way. Rather, they hold within themselves some very practical systematic consequences for the stories we tell about ourselves, others, our communities, and our world. That is to say, if we think clearly enough about where ideas come from, we may learn something important about how to create and tell better stories about ourselves, and we may improve the quality of our lives in the process.

So what better place to start than with one of the oldest and most often repeated stories about the first bite from the apple of knowledge? The Western cultural imagery associated with erotic sexuality and knowledgeable experience goes back at least to Eve, the apple, the Tree of Knowledge, and the serpent, in the Garden of Eden. This imagery is complemented by the self-described role of the ancient Greek philosopher, Socrates, as a midwife of ideas. Students still give apples to their teachers as symbols of knowledge, and a popular line of computers originally targeting the education market is named for the fruit of knowledge. The Socratic method is still taught, and charges teachers with helping students to give birth to fully formed ideas able take on lives of their own.

Socrates went further and said that we are enthralled with meaning in the same way a lover is captivated by the beloved. By definition, attention focuses on what is meaningful, as we ignore 99.99% of incoming sensory data. Recognition, by definition, is re-cognition, a seeing-again of something already known, usually something that has a name. Things that don’t have names are very difficult to see, so things come into language in special ways, via science or poetry. And the names of things focus our attention in very specific ways. Just as “weed” becomes a generic name for unwanted wild plants that might have very desirable properties, so, too, does “man” as a generic name for humans restrict thinking about people to males. The words we use very subtly condition our perceptions and behaviors, since, as Socrates put it, we are captivated by them.

The vital importance of sexuality to the reproductive potential of the species is evident in the extent to which it has subliminally been incorporated into the syntax, semantics, and grammar of language. Metaphoric images of procreation and reproduction so thoroughly permeate culture and language that the verb “to be” is referred to as the copula. New ideas brought into being via a copulative relation of subject and object accordingly are said to have been conceived, and are called concepts. One is said to be pregnant with an idea, or to have the seed or germ of an idea. Questions are probing, penetrating, or seminal. Productive minds are fertile or receptive. The back-and-forth give-and-take of conversation is referred to as social intercourse, and intercourse is the second definition in the dictionary for commerce. Dramatic expositions of events are said to climax, or to result in an anti-climax. Ideas and the narrative recounting of them are often called alluring, captivating, enchanting, spellbinding, or mesmerizing, and so it is that one can in fact be in love with an idea.

Philosophers, feminists, and social theorists have gone to great lengths in exploring the erotic in knowing, and vice versa. Luce Irigaray’s meditations on the fecund and Alfred Schutz’s reflections on our common birth from women both resonate with Paul Ricoeur’s examination of the choice between discourse and violence, which hinges on caring enough to try to create shared meaning. In all of these, we begin from love. Such a hopeful focus on nurturing new life stands in the starkest contrast with the existentialist elevation of death as our shared end.

Cultural inhibitions concerning sexuality can be interpreted as regulating it for the greater good. But Western moral proscriptions typically take a form in which sexuality is regarded as a kind of animal nature that must be subjugated in favor of a higher cultural or spiritual nature. In this world view, just as the natural environment is to be dominated and controlled via science and industry, sexual impulses are controlled, with the feminine relegated to a secondary and dangerous status.

Though promiscuity continues to have destructive effects on society and personal relationships, significant strides have been taken toward making sexual relations better balanced, with sex itself considered an essential part of health and well-being. Puritanical attitudes reject sexual expression and refuse to experience fully this most ecstatic way in which we exist, naturally. But accepting our nature, especially that part of it through which we ensure the continuity of the species, is essential to reintegrating nature and culture.

Finding that sexuality permeates every relationship and all communication is a part of that process. The continuity of the species is no longer restricted to concern with biological reproduction. We must learn to apply what we know from generations of experience with sexual, family, and social relationships in new ways, at new levels of complexity. In the same way that lovemaking is an unhurried letting-be that lingers in caring caresses mutually defining each lover to the other, so must we learn to see analogous, though less intense, ways of being together in every form of communion characteristic of communication and community. Love does indeed make the world go round.

Commerce and Science

There are many encouraging signs suggesting that new possibilities may yet be born of old, even ancient, ideas and philosophies. Many have observed over the last several decades that a new age is upon us, that the modern world’s metaphor of a clockwork universe is giving way to something less deterministic and warmer, less alien and more homey. In many respects, what the paradigm shift comes down to is a recognition that the universe is not an inanimate machine but an intelligent living system. Cold, hard, facts are being replaced with warm, resilient ones that are no less objective in the way they assert themselves as independent entities in the world.

In tune with this shift, increasing numbers of businesses and governments are realizing that long term profitability depends on good relationships with an educated and healthy workforce in a stable sociopolitical context, and with respect to the irreplacable environmental services provided by forests, watersheds, estuaries, fisheries, and ecological biodiversity. As Senge (in de Geus, 1997, p. xi) points out,

In Swedish, the oldest term for ‘business’ is narings liv, literally ‘nourishment for life.’ The ancient Chinese characters for ‘business,’ [are] at least 3,000 years old. The first of these characters translates as ‘life’ or ‘live.’ It can also be translated as ‘survive’ and ‘birth.’ The second translates as ‘meaning.’

Ready counterparts for these themes are deeply rooted in the English language. Without being aware of it, without having made any scholarly inquiry into Socrates’ maieutic arts, virtually every one of us already knows everything we need to know about the birth of living meaning. In any everyday assertion that something is such and so, in linking any subject with a predicate, we re-enact a metaphor of reproductive success in the creation of new meaning.

And here, at the very center of language and communication, the reproduction of meaning in conversation requires a copulative act, a conjugal relation, a coupling of subjects and objects via predicates. The back and forth movement of social intercourse is the deep structure that justifies and brings out its full discursive meaning as a pleasurable and productive process that involves probing, seminal questions; conceiving, being pregnant with, and Socratically midwifing ideas; dramatic climaxes; and a state of enchantment, hypnosis, or rapture that focuses attention and provokes passionate engagement.

When has an idea been successfully midwifed and come to life? We know an idea has come to life when we can restate it in our own words and obtain the same result. We know an idea has come to life when we can communicate it to someone else and they too can apply it in their own terms in new situations.

In his book on resolving the mystery of capital, De Soto points out that living capital can be acted on in banks and courts because it is represented abstractly in instruments like titles and deeds. Dead capital, in contrast, for which legal title does not exist, cannot be used as the basis for a mortgage or a small business loan, nor can one claim a right to the property in court.

Similarly, electrical appliances and machinery are living capital because they work the same way everywhere they can be connected to a standardized power grid by trained operators who have access to the right tool sets. Before the advent of widely shared standards, however, something as simple as different sized hoses and connections on hydrants allowed minor disasters to become catastrophes when fire trucks from different districts responding to an alarm were unable to put their available tools to use.

The distinction between dead and living capital is ultimately scientific, metrological, and mathematical. In ancient Greece, geometrical and arithmetical conversations were the first to be referred to as mathematical because they regularly arrive at the same conclusions no matter who the teacher and student are, and no matter which particular graphical or numerical figures are involved. That is, living meaning is objective; it stays the same, within a range of error, independent of the circumstances in which it is produced.

We can illustrate the conception, gestation, and birth of meaning in terms that lead directly to powerful methods of measurement using tests, assessments, and surveys. In yet another instance of linguistic biomimicry, the mathematical word “matrix” is derived from the ancient Greek word for womb. The matrix of observations recorded from the interaction of questions and answers is the fertile womb in which new ideals are conceived and gestated, and from which they are midwifed.

How? The monotony of the repeated questions and answers in the dialogue reveals the inner logic of the way the subject matter develops. By constantly connecting and reconnecting with the partner in dialogue, Socrates ensures that they stay together, attending to the same object. The reiterated yesses allow the object of the conversation to play itself out through what is said.

Conversational objects can exhibit strongly, and even strikingly, constant patterns of responses across different sets of similar questions posed at different times and places to different people by different interviewers, teachers, or surveyers. We create an increased likelihood of conceiving and birthing living meaning when questions are written in a way that enables them all to attend to the same thing, when they are asked of people also able to attend to that conversational object, and when we score the responses consistently as indicating right or wrong, agree or disagree, frequent or rare, etc.

When test, assessment, and survey instruments are properly designed, they bring meaning to life. They do so by making it possible to arrive at the same measure (the same numeric value, within a small range) for a given amount (of literacy, numeracy, health, motivation, innovation, trustworthiness, etc.) no matter who possesses it and no matter which particular collection of items or instrument is used to measure it. For numbers to be meaningful, they have to represent something that stays the same across particular expressions of the thing measured, and across particular persons measured.

We typically think of comparability in survey or testing research as requiring all respondents or examinees to answer the same questions, but this has not been true in actual measurement practice for decades. The power grid, electrical outlets, and appliances are all constructed so as to work together seamlessly across the vast majority of variations in who is using them, when and where they are used, what they are used for, and why they are used. In parallel fashion, educators are increasingly working to ensure that books, reading tests, and instructional curricula also work together no matter who publishes or administers them, or who reads them or who is measured by them.

The advantages of living literacy capital, for instance, go far beyond what can be accomplished with dead literacy capital. When each teacher matches books to readers using her or his personal knowledge, opportunities for uncontrolled variation emerge, and many opportunities for teachers to learn from each other are closed off. When each teacher’s tests are scored in terms of test-dependent counts of correct answers, knowing where any given child stands relative to the educational objectives is made unnecessarily difficult.

In contrast with these dead capital metrics, living literacy capital, such as is made available by the Lexile Framework for Reading and Writing (www.lexile.com), facilitates systematic comparisons of reading abilities with text reading difficulties, relative to different rates of reading comprehension. Instruction can be individualized, which acknowledges and addresses the fact that any given elementary school classroom typically incorporates at least four different grade levels of reading ability.

Reading is thereby made more enjoyable, both for students who are bored by the easiness of the standard classroom text and for those who find it incomprehensible. Testing is transformed from a pure accountability exercise irrelevant to instruction into a means of determining what a child knows and what can optimally be taught next. Growth in reading can be plotted, not only within school years but across them. Students can move from one school to another, or from grade to grade, without losing track of where they stand on the continuum of reading ability, and without unnecessarily making teachers’ lives more difficult.

In the context of living literacy capital, publishers can better gauge the appropriateness of their books for the intended audiences. Teachers can begin the school year knowing where their students stand relative to the end-of-year proficiency standard, can track progress toward it as time passes, and can better ensure that standards are met. Parents can go online, with their children, to pick out books at appropriate reading levels for birthday and holiday gifts, and for summer reading.

Plainly, what we have achieved with living literacy capital is a capacity to act on the thing itself, literacy, in a manner that adheres to the Golden Rule, justly and fairly treating each reader the way any other reader would want to be treated. In this system of universally uniform and ubiquitously accessible metrics, we can act on literacy itself, instead of confusing it with the reading difficulty of any particular text, the reading ability of any particular student, or any interaction between them. In the same way that titles and deeds make it possible to represent owned property in banks and courts abstractly, so, too, does a properly conceived, calibrated, and distributed literacy metric enable every member of the species of literate humans to thrive in ecological niches requiring an ability to read as a survival skill.

The technical means by which literacy capital has been brought to life should be applied to all forms of human, social, and natural capital. Hospital, employment, community, governance, and environmental quality, and individual numeracy, health, functionality, motivation, etc. are all assessed using rating systems that largely have not yet been calibrated, much less brought together into frameworks of shared uniform metric standards. The body of research presenting instrument calibration studies is growing, but much remains to be done. All of the prior posts in this blog and all of my publications, from the most technical to the most philosophical, bear on the challenging problems we face in becoming stewards of living meaning.

The issues are all of a piece. We have to be the change we want to make happen. It won’t work if we mechanically separate what is organically whole. There’s nothing to do but to keep buzzing those beautiful flowers blooming in the fields, pollinating them and bringing back the bits of nourishment that feed the hive. In this way, this season’s fruit ripens, the seeds of new life take shape, and may yet be planted to grow in fertile fields.

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