Posts Tagged ‘environment’

Cartesian problems cannot be solved by Cartesian solutions, no matter where those solutions originate

April 13, 2019

Trying to persuade or educate individuals to change the way they think and act, by pointing to the facts or by making emotional or moral appeals, seems always and everywhere to be the default go-to solution for those interested in addressing social and environmental problems. I suppose that approach works to varying degrees for different issues, but behavior change never occurs on as massive a scale as when it is mediated by a technology that enables people to do something they value.

The meaning of McLuhan’s expression, “the medium is the message,” and the long history of the many ways in which technologies transform cultures, for better and for worse, all seem utterly lost and forgotten when it comes to efforts aimed at provoking culture change. The ongoing discourses of environmental and social justice inevitably always seem to come back to targeting individual decisions and behaviors as the only recourse for effecting change.

But history teaches us that, if we want to change our values, we have to figure out how to embed the new terms in virally communicable metaphors that enthrall imaginations and captivate people’s attention and interest. Cultures turn on shared meanings that make some behaviors more likely than others. Good metaphors (“love is a rose;” “God is love”) organize experience in ways that allow infinite creative variations on the theme while also lending just a bit of structure and predictability to how things play out. We need to root new metaphors embodying shared human values in information infrastructures that operationalize consensus standards as the common currencies in which those values circulate.

Though the ongoing culture wars seem to suggest wildly divergent values in play across communities, research in developmental psychology strongly indicates that these differences are not what they seem. No matter what their politics, people need to feel valued, to have stable identities, to be recognized as someone of worth, to have a place of dignity in a community, to be trusted, and to see that others enjoy all of these qualities as well. Experience shows that these conditions cannot be implemented by a simple decree or force of will. Broad general conditions have to be cultivated in ways that make the emergence of abundant social capital resources more likely.

A point of entry into thinking about how those conditions might be created is provided by a 2010 quote in the Miami Herald from Gus Speth, former Dean of the Yale School of Forestry and Environmental Studies ( Speth recounts his sense that scientific solutions to ecosystem and climate problems are insufficient because the actual causes of the problems are greed, selfishness, and apathy. So he appeals to religious leaders for help.

But Speth’s moral diagnosis is as misconceived and uninformed as his original scientific one. As has been the topic of multiple posts in this blog, many of today’s problems cannot be solved using the same kind of Cartesian dualist thinking that was used in creating those problems. Voluminous citations in those earlier posts tap a large literature in the philosophy, history, and social studies of science describing a diverse array of examples of nondualist ecosystem thinking and acting (for instance, see references below). These works show how technological media fuse, embody, distribute, and enact social, moral, aesthetic, economic, and scientific values in complex multilevel metasystems (systems of systems). Moral values of fairness, for instance, are embedded in the quantitative values of measurement technologies exported from laboratories into markets where they inform economic values in trade.

Our task is to learn from these examples so that we can develop and deploy new languages that resonate with new values in analogous ways across similarly diverse cultural domains. Beauty, meaning, and poetry have to be as important as logic, mathematics, and science. Readily available theory and evidence already show how all of these are playing their roles in the evolving cultural transformation.

And, fortunately for humanity as well as for the earth, the new nondualist noncartesian solutions will not and cannot be primarily an outcome of deliberate intentions and conscious willpower. On the contrary, these integrated problem-solution monads are living, organic, self-organizing embodiments of ideas that captivate imaginations and draw creative, entrepreneurial energies in productive directions.

Of course, this kind of thing has happened many times in the past, though it has not previously emerged as a result of the kind of cultivated orchestration occurring today. Williamson, North, Ostrom, Coase, and others describe the roles institutions have played in setting up the rules, roles, and responsibilities of efficient markets. Today, new institutions are arising in a context of reproducible scientific results supporting ownership of, investments in, and profits harvested from sustainable impacts measured and managed via virally communicable media spreading social contagions of love and care. This is coming about because we all seek and value meaning and beauty right along with the capacity to enjoy life, liberty, and prosperity. However differently we each define and experience meaning and beauty, caring for the unity and sameness of the objects of the conversations that we are enables us to balance harmonies and dissonances in endless variations performed by every imaginable kind of rhythmic and melodic musical ensemble.

So instead of expecting different results from repeated applications of the same dualistic thinking that got us into today’s problems, we need to think and act nondualistically. Instead of assuming that solutions do not themselves already presuppose and embody problems of a certain type, we need to think in terms of integrated problem-solution monads deployed throughout ecosystems like species in symbiotic relationships. This is precisely what’s happened historically with the oil-automobile-highway-plastics-engineering ecosystem, and with the germ-disease-pharmaceutical-public health-medicine ecosystem. In each case, financial, market, accounting, regulatory, legal, educational, and other institutions evolved in tandem with the emerging sociotechnical ecology.

Now we face urgent needs to think and act on previously unheard of scales and levels of complexity. We have to work together and coordinate efforts in social and psychological domains with no previous history of communications capable of functioning at the needed efficiencies.

But merely urging people to live differently will never result in the changes that must be brought about. No matter how compelling the facts, no matter how persuasive the emotional power, and no matter how inspirational the moral argument, individual people and small groups simply cannot create new shared standards of behavior out of thin air. We are all products of our times and our sociocultural environments. People cannot be expected to simply wake up one day and spontaneously transform their habits by an effort of will. Instead, the values of fairness, equity, inclusion, and justice we say we live by must be embedded within the very fabric of everyday life, the way hours, meters, liters, degrees, grams, and volts are now.

That is, measurements read off instruments calibrated in fair units of comparison—measurements mathematically equivalent to those made with the scales of justice, measurements expressed in the common metrics of a new international system of units, and measurements as adaptable to local individual improvisations as they are generally comparable and navigable—have to be built into every institution in just the same way existing units of measurement are. Education, health care, social services, human resource management, environmental solutions—all of these and more need to attend closely to ways in which the objects of conversation can be more systematically expressed in meaningful words. Ecosystem thinking demands that everyone and everything in a system of relationships must be consistently kept in proportionate contact, within ranges of reported uncertainty, instead of being disconnected off into separate incommensurable universes of discourse, as occurs in today’s institutions.

These are all monumentally huge challenges. But much of the hardest work has been underway for decades, with important results and resources spreading into widely used applications often taken for granted in the background of largely unexamined assumptions. These results are now well enough established, and the associated social and environmental problems are so serious, that more can and should be done to put them to use.

The need for new values is indeed urgent, but empty talk and doing more of the same is getting us nowhere, at best, and more often is worsening conditions. Conceptual determinations of reproducible mathematical values embodying people’s lived social and moral values in fungible economic values are not just theoretical possibilities or provisional experimental results. They are longstanding, widely available, and practical, as well as beautiful and meaningful. With attentive cultivation and nurturing, there are abundant reasons for believing in a safe, healthy, happy, and prosperous future for humanity and life on earth.


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Fisher, W. P., Jr. (2012). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

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Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174.

Fisher, W. P., Jr. (2019). How beauty teaches us to understand meaning, in revision.

Fisher, W. P., Jr. (2019). A nondualist social ethic: Fusing subject and object horizons in measurement. TMQ–Techniques, Methodologies, and Quality, in press.

Fisher, W. P., Jr., & Cavanagh, R. (2016). Measurement as a medium for communication and social action, I & II. In Q. Zhang & H. H. Yang (Eds.), Pacific Rim Objective Measurement Symposium (PROMS) 2015 Conference Proceedings (pp. 153-182). Berlin: Springer-Verlag.

Fisher, W. P., Jr., & Oon, E. P.-T. (2019). Information coherence and complexity across contexts: Negotiating discontinuities in educational assessment infrastructures. Information Systems Research, in review.

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Fisher, W. P., Jr., Oon, E. P.-T., & Benson, S. (2019). Rethinking the role of educational assessment in classroom communities: How can design thinking address the problems of coherence and complexity? Measurement, in review.

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Making sustainability impacts universally identifiable, individually owned, efficiently exchanged, and profitable

February 2, 2019

Sustainability impacts plainly and obviously lack common product definitions, objective measures, efficient markets, and associated capacities for competing on improved quality. The absence of these landmarks in the domain of sustainability interests is a result of inattention and cultural biases far more than it is a result of the inherent characteristics or nature of sustainability itself. Given the economic importance of these kinds of capacities and the urgent need for new innovations supporting sustainable development, it is curious how even those most stridently advocating new ways of thinking seem to systematically ignore well-established opportunities for advancing their cause. The wealth of historical examples of rapidly emerging, transformative, disruptive, and highly profitable innovations would seem to motivate massive interest in how extend those successes in new directions.

Economists have long noted how common currencies reduce transaction costs, support property rights, and promote market efficiencies (for references and more information, see previous entries in this blog over the last ten years and more). Language itself is well known for functioning as an economical labor-saving device in the way that useful concepts representing things in the world as words need not be re-invented by everyone for themselves, but can simply be copied. In the same ways that common languages ease communication, and common currencies facilitate trade, so, too, do standards for common product definitions contribute to the creation of markets.

Metrologically traceable measurements make it possible for everyone everywhere to know how much of something in particular there is. This is important, first of all, because things have to be identifiable in shared ways if we are to be able to include them in our lives, socially. Anyone interested in obtaining or producing that kind of thing has to be able to know it and share information about it as something in particular. Common languages capable of communicating specifically what a thing is, and how much of it there is, support claims to ownership and to the fruits of investments in entrepreneurial innovations.

Technologies for precision measurement key to these communications are one of the primary products of science. Instruments measuring in SI units embody common currencies for the exchange of scientific capital. The calibration and distribution of such instruments in the domain of sustainability impact investing and innovation ought to be a top-level priority. How else will sustainable impacts be made universally identifiable, individually owned, efficiently exchanged, and profitable?

The electronics, computer, and telecommunications industries provide ample evidence of precision measurement’s role in reducing transaction costs, establishing common product definitions, and reaping huge profits. The music industry’s use of these technologies combines the science and economics of precision measurement with the artistic creativity of intensive improvisations constructed from instruments tuned to standardized scales that achieve wholly unique levels of individual innovation.

Much stands to be learned, and even more to be gained, in focusing sustainability development on ways in which we can harness the economic power of the profit motive by combining collective efforts with individual imaginations in the domains of human, social, and natural capital. Aligning financial, monetary wealth with the authentic wealth and genuine productivity of gains in human, community, and environmental value ought to be the defining mission of this generation. The time to act is now.

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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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Current events in metrology for fun, profitable, and self-sustaining sustainability impacts

September 18, 2018

At the main event I attended last week at the Global Climate Action Summit in San Francisco, the #giveyouthachance philanthropic gathering at the Aquarium of the Bay, multiple people independently spoke to aligning social and environmental values with financial values, and explicitly stated that economic growth does not automatically entail environmental degradation.

As my new buddy David Traub (introduced as a consequence of the New Algorithm event in Stockholm in June with Angelica Lips da Cruz) was the MC, he put me on the program at the last minute, and gave me five minutes to speak my piece in a room of 30 people or so. A great point of departure was opened up when Carin Winter of spoke to her work in mindfulness education and led a guided meditation. So I conveyed the fact that the effects of mindfulness practice are rigorously measurable, and followed that up with the analogy from music (tuning instruments to harmonize relationships),  with the argument against merely shouldering the burden of costs because it is the right thing to do, with the counter-argument for creating efficient competitive markets for sustainable impacts, and with info on the previous week’s special session on social and psychological metrology at IMEKO in Belfast. It appeared that the message of metrology as a means for making sustainability self-sustaining, fun, and profitable got through!

Next up: Unify.Earth has developed their own new iteration on blockchain, which will be announced Monday, 24 September, at the UN SDG Media Center (also see here) during the World Economic Forum’s Sustainable Development Impact Summit. The UEX (Unify Earth Exchange) fills the gap for human capital stocks left by the Universal Commons‘ exclusive focus on social and natural capital.

So I’ve decided to go to NY and have booked my travel.

Back in February, Angelica Lips da Cruz recounted saying six months before that it would take two years to get to where we were at that time. Now another seven months have passed and I am starting to feel that the acceleration is approaching Mach 1! At this rate, it’ll be the speed of light in the next six months….

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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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Self-Sustaining Sustainability, Once Again, Already

August 12, 2018

The urgent need for massive global implementations of sustainability policies and practices oddly and counterproductively has not yet led to systematic investments in state of the art sustainability metric standards. My personal mission is to contribute to meeting this need. Longstanding, proven resources in the art and science of precision instrumentation calibration and explanatory theory are available to address these problems. In the same way technical standards for measuring length, mass, volume, time, energy, light, etc. enable the coordination of science and commerce for manufactured capital and property, so, too, will a new class of standards for measuring human, social, and natural capital.

This new art and science contradicts common assumptions in three ways. First, contrary to popular opinion that measuring these things is impossible, over 90 years of research and practice support a growing consensus among weights and measures standards engineers (metrologists) and social and psychological measurement experts that relevant unit standards are viable, feasible, and desirable.

Common perceptions are contradicted in a second way in that measurement of this kind does not require reducing human individuality to homogenized uniform sameness. Instead of a mechanical metaphor of cogs in a machine, the relevant perspective is an organic or musical one. The goal is to ensure that local uniqueness and creative improvisations are freely expressed in a context informed by shared standards (like DNA, or a musical instrument tuning system).

The third way in which much of what we think we know is mistaken concerns how to motivate adoption of sustainability policies and practices. Many among us are fearful that neither the general population nor its leaders in government and business care enough about sustainability to focus on implementing solutions. But finding the will to act is not the issue. The problem is how to create environments in which new sustainable forms of life multiply and proliferate of their own accord. To do this, people need means for satisfying their own interests in life, liberty, and the pursuit of happiness. The goal, therefore, is to organize knowledge infrastructures capable of informing and channeling the power of individual self-interest. The only way mass scale self-sustaining sustainable economies will ever happen is by tapping the entrepreneurial energy of the profit motive, where profit is defined not just in financial terms but in the quality of life and health terms of authentic wealth and genuine productivity.

We manage what we measure. If we are to collectively, fluidly, efficiently, and innovatively manage the living value of our human, social, and natural capital, we need, first, high quality information expressed in shared languages communicating that value. Second, we need, to begin with, new scientific, legal, economic, financial, and governmental institutions establishing individual rights to ownership of that value, metric units expressing amounts of that value, conformity audits for ascertaining the accuracy and precision of those units, financial alignments of the real value measured with bankable dollar amounts, and investment markets to support entrepreneurial innovations in creating that value.

The end result of these efforts will be a capacity for all of humanity to pull together in common cause to create a sustainable future. We will each be able to maximize our own personal potential at the same time we contribute to the greater good. We will not only be able to fulfill the potential of our species as stewards of the earth, we will have fun doing it! For technical information resources, see below. PDFs are available on request, and can often be found freely available online.

Self-Sustaining Sustainability

Relevant Information Resources

William P. Fisher, Jr., Ph.D.

Barney, M., & Fisher, W. P., Jr. (2016). Adaptive measurement and assessment. Annual Review of Organizational Psychology and Organizational Behavior, 3, 469-490.

Fisher, W. P., Jr. (1997). Physical disability construct convergence across instruments: Towards a universal metric. Journal of Outcome Measurement, 1(2), 87-113.

Fisher, W. P., Jr. (1999). Foundations for health status metrology: The stability of MOS SF-36 PF-10 calibrations across samples. Journal of the Louisiana State Medical Society, 151(11), 566-578.

Fisher, W. P., Jr. (2000). Objectivity in psychosocial measurement: What, why, how. Journal of Outcome Measurement, 4(2), 527-563.

Fisher, W. P., Jr. (2002). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [].

Fisher, W. P., Jr. (2003). The mathematical metaphysics of measurement and metrology: Towards meaningful quantification in the human sciences. In A. Morales (Ed.), Renascent pragmatism: Studies in law and social science (pp. 118-153). Brookfield, VT: Ashgate Publishing Co.

Fisher, W. P., Jr. (2004). Meaning and method in the social sciences. Human Studies: A Journal for Philosophy & Social Sciences, 27(4), 429-454.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [].

Fisher, W. P., Jr. (2009, November 19). Draft legislation on development and adoption of an intangible assets metric system. Living Capital Metrics blog:

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

Fisher, W. P., Jr. (2009). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital ( Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2010, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities., Sausalito, California.

Fisher, W. P., Jr. (2010). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital. Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University (

Fisher, W. P., Jr. (2010). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics Conference Series, 238(1), 012016.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In N. Brown, B. Duckor, K. Draney & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 2 (pp. 1-27). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr. (2012). Measure and manage: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. 43-63). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [].

Fisher, W. P., Jr. (2015). A probabilistic model of the law of supply and demand. Rasch Measurement Transactions, 29(1), 1508-1511 [].

Fisher, W. P., Jr. (2015). Rasch measurement as a basis for metrologically traceable standards. Rasch Measurement Transactions, 28(4), 1492-1493 [].

Fisher, W. P., Jr. (2015). Rasch metrology: How to expand measurement locally everywhere. Rasch Measurement Transactions, 29(2), 1521-1523.

Fisher, W. P., Jr. (2017, September). Metrology, psychometrics, and new horizons for innovation. 18th International Congress of Metrology, Paris, 10.1051/metrology/201709007.

Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174.

Fisher, W. P., Jr. (2018). How beauty teaches us to understand meaning. Educational Philosophy and Theory, in review.

Fisher, W. P., Jr. (2018). Separation theorems in econometrics and psychometrics: Rasch, Frisch, two Fishers, and implications for measurement. Scandinavian Economic History Review, in review.

Fisher, W. P., Jr., Harvey, R. F., & Kilgore, K. M. (1995). New developments in functional assessment: Probabilistic models for gold standards. NeuroRehabilitation, 5(1), 3-25.

Fisher, W. P., Jr., Harvey, R. F., Taylor, P., Kilgore, K. M., & Kelly, C. K. (1995). Rehabits: A common language of functional assessment. Archives of Physical Medicine and Rehabilitation, 76(2), 113-122.

Fisher, W. P., Jr., & Stenner, A. J. (2011, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series).National Science Foundation:

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium,, Jena, Germany.

Fisher, W. P., Jr., & Stenner, A. J. (2016). Theory-based metrological traceability in education: A reading measurement network. Measurement, 92, 489-496.

Fisher, W. P., Jr., & Wilson, M. (2015). Building a productive trading zone in educational assessment research and practice. Pensamiento Educativo: Revista de Investigacion Educacional Latinoamericana, 52(2), 55-78.

Pendrill, L., & Fisher, W. P., Jr. (2013). Quantifying human response: Linking metrological and psychometric characterisations of man as a measurement instrument. Journal of Physics Conference Series, 459, 012057.

Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, 71, 46-55.


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Self-Sustaining Sustainability

August 6, 2018

After decades of efforts and massive resources expended in trying to create a self-sustaining sustainable economy, perhaps it is time to wonder if we are going about it the wrong way. There seems to be truly significant and widespread desire for change, but the often inspiring volumes of investments and ingenuity applied to the problem persistently prove insufficient to the task. Why?

I’ve previously and repeatedly explained how finding the will to change is not the issue. This time I’ll approach my proposed solution in a different way.

Q: How do we create a self-sustaining sustainable economy?

A: By making sustainability profitable in monetary terms as well as in the substantive real terms of the relationships we live out with each other and the earth. Current efforts in this regard focus solely on reducing energy costs enough to compensate for investments in advancing the organizational mission. We need far more comprehensively designed solutions than that.

Q: How do we do that?

A: By financially rewarding improved sustainability at every level of innovation, from the individual to the community to the firm.

Q: How do we do that?

A: By instituting rights to the ownership of human, social, and natural capital properties, and by matching the demand for sustainability with the supply of it in a way that will inform arbitrage and pricing.

Q: How do we do that?

A: By lowering the cost of the information needed to be able to know how many shares of human, social, and natural capital stocks are owned, and to match demand with supply.

Q: How could that be done?

A: By investing as a society in improving the quality and distribution of the available information.

Q: What does that take?

A: Creating dependable and meaningful tools for ascertaining the quantity, quality, and type of sustainability impacts on human, social, and natural capital being offered.

Q: Can that be done?

A: The technical art and science of measurement needed for creating these tools is well established, having been in development for almost 100 years.

Q: How do we start?

A: An important lesson of history is that building the infrastructure and its array of applications follows in the wake of, and cannot precede, the institution of the constitutional ideals. We must know what the infrastructure and applications will look like in their general features, but nothing will ever be done if we think we have to have them in place before instantiating the general frame of reference. The most general right to own legal title to human, social, and natural capital can be instituted, and the legal status of new metric system units can be established, before efforts are put into unit standards, traceability processes, protocols for intralaboratory ruggedness tests and interlaboratory round robin trials, conformity assessments, etc.

Q: It sounds like an iterative process.

A: Yes, one that must attend from the start to the fundamental issues of information coherence and complexity, as is laid out in my recent work with Emily Oon, Spencer Benson, Jack Stenner, and others.

Q: This sounds highly technical, utilitarian, and efficient. But all the talk of infrastructure, standards, science, and laboratories sounds excessively technological. Is there any place in this scheme for ecological values, ethics, and aesthetics? And how are risk and uncertainty dealt with?

A: We can take up each of these in turn.

Ecological values: To use an organic metaphor, we know the DNA of the various human, social, and natural capital forms of life, or species, and we know their reproductive and life cycles, and their ecosystem requirements. What we have not done is to partner with each of these species in relationships that focus on maximizing the quality of their habitats, their maturation, and the growth of their populations. Social, psychological, and environmental relationships are best conceived as ecosystems of mutual interdependencies. Being able to separate and balance within-individual, between-individual, and collective levels of complexity in these interdependencies will be essential to the kinds of steward leadership needed for creating and maintaining new sociocognitive ecosystems. Our goal here is to become the change we want to institute, since caterpillar to butterfly metamorphoses come about only via transformations from within.

Ethics: The motivating intention is to care simultaneously and equally effectively for both individual uniqueness and global humanity. In accord with the most fundamental ethical decision, we choose discourse over violence, and we do so by taking language as the model for how things come into words. Language is itself alive in the sense of the collective processes by which new meanings come into it. Language moreover has the remarkable capacity of supporting local concrete improvisations and creativity at the same time that it provides navigable continuity and formal ideals. Care for the unity and sameness of meaning demands a combination of rigorous conceptual determinations embodied in well-defined words with practical applications of those words in local improvisations. That is how we support the need to make decisions with inevitably incomplete and inconsistent information while not committing the violence of the premature conclusion. The challenge is one of finding a balance between openness and boundaries that allows language and our organizational cultures to be stable while also evolving. Our technical grasp of complex adaptive systems, autopoiesis, and stochastic measurement information models is advanced enough to meet these ethical requirements of caring for ourselves, each other, and the earth.

Aesthetics: An aesthetic desire for and love of beauty roots the various forms of life inhabiting diverse niches in the proposed knowledge ecosystem and information infrastructure, and does so in the ground of the ethical choice of discourse and meaning over violence. The experience of beauty teaches us how to understand meaning. The attraction to beauty is a unique human phenomenon because it combines apparent opposites into a single complex feeling. Even when the object of desire is possessed as fully as possible, desire is not eliminated, and even when one feels the object of desire to be lost or completely out of touch, its presence and reality is still felt. So, too, with meaning: no actual instance of anything in the world ever embodies the fullness of an abstract conceptual ideal. This lesson of beauty is perhaps most plainly conveyed in music, where artists deliberately violate the standards of instrument tuning to create fascinating and absorbing combinations of harmony and dissonance from endlessly diverse ensembles. Some tunings persist beyond specific compositions to become immediately identifiable trademark sounds. In taking language as a model, the aesthetic combination of desire and possession informs the ethics of care for the unity and sameness of meaning, and vice versa. And ecological values, ethics, and aesthetics stand on par with the technical concerns of calibration and measurement.

Risk and uncertainty: Calibrating a tool relative to a unit standard is by itself already a big step toward reducing uncertainty and risk. Instead of the chaos of dozens of disconnected sustainability indicators, or the cacophony of hundreds or thousands of different tests, assessments, or surveys measuring the same things, we will have data and theory supporting interpretation of reproducible patterns. These patterns will be, and in many cases already are, embodied in instruments that further reduce risk by defining an invariant unit of comparison, simplifying interpretation, reducing opportunities for mistakes, by quantifying uncertainty, and by qualifying it in terms of the anomalous exceptions that depart from expectations. Each of these is a special feature of rigorously defined measurement that will eventually become the expected norm for information on sustainability.

For more on these themes, see my other blog posts here, my various publications, and my SSRN page.


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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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A Summary End-of-Year Philosophical Overview

December 25, 2009

So the end of the year and the start of a new one makes a good time to reflect a bit on just what the situation in the world looks like, philosophically speaking.

As is so often the case, we hold the keys to our own liberation, but don’t know it, can’t see them, or refuse out of pure contrariness to fit them in the locks. Here, then, is a list of locks and keys for those who might want to match them up and see new ways of doing things.

  • The way we define a problem sets up a class of solutions as a restricted range of ways that things can be done. Historians and philosophers of science have shown that, contrary to the way we usually think of things, solutions come first. As the old expression goes, “When the only tool you have is a hammer, everything looks like a nail.” Science is so dependent on the available technology for the way it defines problems that this point has led to the emergence of the term “technoscience” as an explicit marker of the difference between this new point of view and the old one (among many works in this area, see Ihde, 1983; Latour, 1987).
  • One of the most ancient human technologies is language itself; the word “text” has the same root in the Sanskrit TEK and Greek techne as technique and textile. Just as is the case with technoscience, before we have the  slightest chance to do anything about it, language prethinks the world for us. In the same way that the Grateful Dead sings about the music playing the band, the words and grammar we use are using us much more than vice versa. We have rightly become more sensitive to the way words restrict our expectations, so that “man” is no longer taken to refer to all people. But the problem is far more complex than this example might lead us to believe. The very way in which words represent things is itself the paradigmatic model for science, as becomes apparent as we think this through.
  • One very important way that language sets us up to think in a particular way stems from the subject-verb-object structure of Western European languages. We habitually define problems in terms of what is sometimes called the Cartesian duality or subject-object split. Our language has led to the perception that thinking subjects are completely separate from and independent of the objects they encounter and act on. The limited framework in which this split can be reasonably entertained has been enormously productive, but has led to equally enormous undesired consequences in terms of human, social, and environmental waste.
  • Descartes himself recognized the limits of separating the thinking subject from the world of objects, but took a pragmatic attitude toward simplifying things. If Descartes hadn’t existed, we would have had to invent him, and to some extent, we probably already have. Descartes (1971, pp. 183-4) understood the situation very well, saying: “I have often observed that philosophers make the mistake of trying to explain by logical definitions those things which are most simple and self-evident; they thus only make them more obscure. When I said that the proposition I experience (cogito) therefore I am is the first and most certain of those we come across when we philosophize in an orderly way, I was not denying that we must first know what is meant by experience, existence, certainty; again, we must know such things as that it is impossible for that which is experiencing to be non-existent; but I thought it needless to enumerate these notions, for they are of the greatest simplicity, and by themselves they can give us no knowledge that anything exists.”
  • Descartes then did not use the phrase ‘cogito, ergo sum’ in the rigid and over-simplified way which is often attributed to him.  Heidegger (1967, p. 104) explains that
    “The formula which the proposition sometimes has, ‘cogito, ergo sum,’ suggests the misunderstanding that it is here a question of inference.  That is not the case and cannot be so, because this conclusion would have to have as its major premise: Id quod cogitat, est; and the minor premise: cogito; conclusion: ergo sum.  However, the major premise would only be a formal generalization of what lies in the proposition: ‘cogito-sum.’ Descartes himself emphasizes that no inference is present.  The sum is not a consequence of the thinking, but vice versa; it is the ground of thinking, the fundamentum.”
  • Today, though, the matters that were too simple for Descartes to concern himself with have become problems of huge proportion.  In a note to Heidegger’s discussion of this passage from Descartes, the editor suggests that the greatest part of Heidegger’s philosophical work has been devoted to enumerating and putting on record what Descartes left out as too simple to be concerned with (Krell in Heidegger 1982b, p. 125).
  • No doubt a great many thinkers and scholars have an intellectual grasp of these issues. Putting those thoughts in action is proving difficult, to say the least. Institutionalized habits of mind seem nearly impossible to overcome. In one of those great ironies of history, we now have a situation in which we are trying to solve a new class of problems (nonCartesian ones) using the approaches that are the cause of the class of problems (Cartesian ones). Of course, as long we insist on operating this way, all we can do is make things worse. (For more on this, see a previous blog describing how the problem is the problem.)
  • We can see our way out of this, and moreover find the motivation to act, by considering how we got into it. Descartes (1961, p. 8) held that “…in seeking the correct path to truth we should be concerned with nothing about which we cannot have a certainty equal to that of the demonstrations of arithmetic and geometry.” In saying this, Descartes identifies himself as a student of Plato, as someone experienced enough in mathematics to have met the requirements for admission to the Academy. Plato wanted students familiar with arithmetic and geometry because they know that numeric and geometric figures plainly are not the mathematical objects they stand for. Geometrical analyses of squares, circles, and triangles always come out the same, no matter which particular figure of a type is involved. Understanding this distinction was fundamental to taking up the study of philosophy, which actually involves nothing but the independence of figure from meaning, of word from concept. The Cartesian duality is a natural extension of Plato into the distinction between mind and body, subject and object.
  • So we look right through the particular words, numbers, and geometrical figures representing things and see the things themselves in terms of abstract ideals that are basically mathematical. But even in naming abstract ideals as such we do not come any closer to grasping or apprehending the complete truth of being. All we have are words, but this does not mean that we are trapped forever in a linguistic cage. The situation is quite the contrary, in fact. Science is poetry in motion. Science is a systematic way of simultaneously inventing and discovering things brought into words via dialogues with life. Science is the way we let the metaphoric process do its thing (among many works in this area, see especially Gerhart & Russell, 1984, and Kuhn, 1993; for an example of recent work, see Colburn & Shute, 2008).
  • Far from controlling and dominating the world, what science enables us to do via metaphor is to subject ourselves systematically to very specific aspects of the world.  Our problem today is not one of overcoming the way we have subdued nature, each other, and ourselves so much as it is one of subjecting ourselves to a more comprehensive range of things about which we can “have a certainty equal to that of the demonstrations of arithmetic and geometry,” as Descartes put it. In other words, how do we extend the power of nonCartesian scientific metaphor-making into the human, social, and environmental sciences? This project has been the focus of my work from the beginning of my professional career to the present, and is elaborated in detail in a number of works (Fisher, 1988, 1992, 2004, 2010b).
  • Though explanations and logic can be compelling to some readers, the real power of ideas is exhibited in practice. Living the change we want to see happen has, for me, involved acting on yet another aspect of the way science poetically extends language’s prethinking of the world. The identity and coherence of a culture or an historical epoch is largely a matter of the way particular metaphors inform a worldview and the paradigmatic objects of the conversations of the time. Individual thoughts and behaviors are coordinated and harmonized via conversations that take place in terms, of course, of the words and concepts in circulation. And so we see that language is the original network that makes collective cognition and action possible. Language is the model for the not-always-so-wise wisdom of crowds effect that synchronizes everything from markets to laboratories to rush hours.
  • Seen from this angle, then, the problem is one of seeing how mathematical clarity can be embodied in the instruments of a technoscience distributed across the nodes of networks. How can we think and act together on the problems of the human, social, and environmental sciences with the same kind of coordination we experience in time via clocks or in the sequencing of the SARS virus via laboratories sharing metrological standards (to cite an example given by Surowiecki (2004), with (Latour, 1987, 2005) in the background)? The answer to this question lies in the calibration of instruments that are linked together and are so traceable to reference standards in a kind of metric system for each major construct of interest, such as the abilities, health, attitudes, trust, and environmental qualities essential to human, social, and natural capital (Fisher, 1996, 2000a, 2000b, 2002, 2005, 2009a, 2009b, 2010a).
  • Instruments are being calibrated on a broad scale across a great many applied and research contexts in business and academic contexts (among thousands of publications, see Bezruczko, 2005; Drehmer, Belohlav, & Coye, 2000; Masters, 2007; Salzberger & Sinkovics, 2006). Though local or proprietary implementations work to coordinate thought and behavior within restricted communities, systematic approaches to creating universally uniform metric systems for human, social, and natural capital are as yet nonexistent (Fisher, 2009a, 2009b).
  • Finally, in accord with our acceptance of the way we are always already caught up in the play and flow of language, what does a nonCartesian approach to facilitating networked harmonizations look like? There are four main features to be aware of. First off, we want to be acutely aware of and vigilantly sensitive to the role of metaphor. In abstracting from individuals to universals, we generalize from particulars in ways that must be justified (Ballard, 1978, pp. 186-190; Ricoeur, 1974; Gadamer, 1991, pp. 7-8).  All generalization involves telling a story that is largely true of everyone and everything that has a part in it, but which simultaneously is not perfectly or exactly true of any of them. As Rasch (1960, p. 115) points out, if force, mass, and acceleration are measured with enough precision we see that the actual measures do not accord exactly with Newton’s laws; rather, their parameters in probability distributions do. Respect and attention to the potential for what Ricoeur (1974) called the violence of the premature conclusion must be brought to bear in systematic ways to aid in “recalling the uniqueness of the person measured” (Ballard, 1978, p. 189). It will be essential to incorporate the ontological method’s (Fisher, 2010b; Heidegger, 1982a, pp. 21-23, 32-330) deconstructive moment as a judicial element in a balance of powers with the legislative moment’s experimentally justified reductions and the executive moment’s constructive applications.
  • Second, attuned to those instances in which the philosophical thesis of the independence of figure and meaning, or the separation of signifier and signified, is difficult to satisfy (Derrida, 1982, p. 229; Wood & Bernasconi, 1988, 88-89), a nonCartesian approach to facilitating network harmonizations requires that we focus on identifying where, when, and what signifier-signified separations can be obtained. Because the universality and objectivity of mathematical objects make them “the absolute model for any object whatsoever” (Derrida, 1989, p. 66, also see p. 27), and because it is number and not word that is the real paradigm of the domain of things that can be understood in language (Gadamer, 1989, p. 412), we now strive to test the limits of the mathematical as “the fundamental presupposition of all ‘academic’ work” and “of the knowledge of things” (Heidegger, 1967, pp. 75-76).  This is the same thing as attending to the calibration of the instruments that are ultimately to be linked to reference standards. This is the domain of Rasch measurement (Andrich, 1988, 2004; Bond & Fox, 2007; Rasch, 1960; Wilson, 2005; Wright, 1997), which takes the assessment of data consistency, unidimensionality, reliability, and construct validity as essential.
  • Third, with calibrated instruments in hand, attention turns to linking and equating them systematically in networks tracing connections to and from metrological reference standards, adapting the methods for maintaining the existing metric system (Fisher, 1996, 2000a, 2000b, 2005, 2009a, 2009b, 2010a). The goal here will be one of coordinating and synchronizing the self-organizing structures of each distinct construct, much as was done for the measurement of literacy (Stenner, et al., 2006).
  • Fourth, though we have to this point completely respected our inescapable immersion in the play of language, there still remains the question of how such a massive transformation from the modern Cartesian dualist point of view to a postmodern nonCartesian one will be brought about. Like any paradigm shift, the new way of doing things emerges as a function of the returns–economic, political, social, and psychological–that can be expected from the investments made. And in accord with the broad qualitative sense of the mathematical as learning through what we already know (Heidegger, 1967; Kisiel, 1973), the new will emerge as an amplification of something old. A great deal of attention and investment is currently being focused on creating whole new sources of sustainable, socially responsible, and long-term profits from closer management of human, social, and natural capital. In the same way that the metric system is an essential component of global trade, and in the same way that origins of the metric system coincide with the scientific, industrial, and political revolutions of the late 18th and early 19th centuries, so, too, will a new metric system for human, social, and natural capital provide a foundation for new efficiencies and degrees of effectiveness across multiple domains. The profit motive is an engine of great energy and resources. We need to learn how to harness it as a driver of growth in realized human potential, social cohesion, and environmental quality. What other way of giving ourselves over to the nonCartesian and playful creation of meaning is there, in fact, except to extend the rule of law and the invisible hand’s matching of supply and demand into all of the areas essential to human being?

Philosophically speaking, then, it would seem that all of the elements are in place for a positive answer to Zimmerman’s (1990, p. 274) question, “can we develop the non-absolutist, non-foundational categories necessary to assess, to confront, and to transform the technological and economic mobilization of humanity and the earth at the beginning of the twenty-first century?” Zimmerman might not agree with my sense that we can, since, reflecting on Heidegger’s efforts to put his political philosophy in action, he (1990, p. 257) remarks that “Heidegger’s political engagement in 1933-34 led him to conclude that all merely human ‘revolutions’ and ‘decisions’ would simply reinforce the system already in play. The question for us is: Is that conclusion tenable?” Zimmerman (pp. 245-246) apparently hopes it is not, and looks to love, compassion, and respect as alternatives to Heidegger’s hope for divine intervention.

But let’s consider what is “merely human.” The nonhuman is not necessarily divine, even if that is what Heidegger might have meant. And has not Heidegger (1962) himself already identified care as the defining characteristic of human being, with Habermas (1995) underscoring “considerateness” for our shared vulnerability, Ricoeur (1974) focusing on the desire for meaning and the choice in favor of discourse over violence, and Gadamer (1991, p. 61) also holding that “the first concern of all dialogical and dialectical inquiry is a care for the unity and sameness of the thing under discussion”? Beyond these are shifts of focus away from death as our common end, and toward our common birth from women as our shared beginning (Fielding, 2003; Schues, 1997; Schutz, 1962, 1966; Tymieniecka 1998, 2000; Zaner, 2002). And even in this, we must inevitably draw from Plato, now in Socrates’ stress on his role as a midwife of ideas, and from Aristotle, who provides the model for how to take possession of the value of living meaning in theory (Gadamer, 1980, p. 200).

Further, the conception, gestation, midwifery, and nurturing of ideas that takes place via considerateness and the desire for meaning were never the product of “merely human” intentions or designs, any more than biological reproduction was. Rather, we submit to the demands of the ways meaning is created to the same extent that we submit to the ways that life is recreated; in both cases, there is such Hegelian joy in the ways we find ourselves in each other that we can hardly complain (though whole cultures have figured out ways of doing so).

And we can indeed fault Heidegger, as Zimmerman (1990, p. 244, 258) does, for having “refused to take seriously the organic dimension of human existence,” and for somehow managing “to ignore the concrete history of actual existence and actual inquiry.”  We arrive at an entirely different, democratic, sphere of political implications (Ihde, 1990; Latour, 2004; Latour & Weibel, 2005), when we extend the deconstruction of metaphysics into examinations of the actual material practices of science, as Latour (1987, 2005) and others have done (Ihde, 1991, 1998; Ihde & Selinger, 2003). The dialogue with nonhuman others (Latour, 1994) is conceived as explicitly nonCartesian and nondualist, such that it is literally impossible to conceive of anything that does not incorporate social relations, or of any social relations that do not incorporate nonhuman others.

The self-organized unfolding of such dialogues play out the self-representative activity of the things themselves, with method defined as their movement in thought (Gadamer, 1989; Fisher, 2004). Reinforcing some aspect or aspects of the system already in play is indeed inevitable, as Heidegger concluded. But no important “revolutions” or “decisions” have ever been based in “merely human” inputs (Latour, 1993), as becomes apparent if we pay close attention to the concrete behaviors and communications through which meaning is created and shared. The “non-absolutist, non-foundational categories necessary to assess, to confront, and to transform the technological and economic mobilization of humanity and the earth at the beginning of the twenty-first century” referred to by Zimmerman are indeed in hand. Though many unfamiliar with the evidence, theory, and instruments may doubt this is true, a contemporary Galileo might be heard to mutter, “E pur si muove!”


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s becomes apparent

Graphic Illustrations of Why Scores, Ratings, and Percentages Are Not Measures, Part One

July 1, 2009

It happens occasionally when I’m speaking to a group unfamiliar with measurement concepts that my audiences audibly gasp at some of the things I say. What can be so shocking about anything as mundane as measurement? A lot of things, in fact, since we are in the strange situation of having valid and rigorous intuitions about what measures ought to be, while we simultaneously have entire domains of life in which our measures almost never live up to those intuitions in practice.

So today I’d like to spell out a few things about measurement, graphically. First, I’m going to draw a picture of what good measurement looks like. This picture will illustrate why we value numbers and want to use them for managing what’s important. Then I’m going to draw a picture of what scores, ratings, and percentages look like. Here we’ll see how numbers do not automatically stand for something that adds up the way they do, and why we don’t want to use these funny numbers for managing anything we really care about. What we will see here, in effect, is why high stakes graduation, admissions, and professional certification and licensure testing agencies have long since abandoned scores, ratings, and percentages as their primary basis for making decisions.

After contrasting those pictures, a third picture will illustrate how to blend the valid intuitions informing what we expect from measures with the equally valid intuitions informing the observations expressed in scores, ratings, and percentages.

Imagine measuring everything in the room you’re in twice, once with a yardstick and once with a meterstick. You record every measure in inches and in centimeters. Then you plot these pairs of measures against each other, with inches on the vertical axis and centimeters on the horizontal. You would come up with a picture like Figure 1, below.

Figure 1. How We Expect Measures to Work

Figure 1. How We Expect Measures to Work

The key thing to appreciate about this plot is that the amounts of length measured by the two different instruments stay the same no matter which number line they are mapped onto. You would get a plot like this even if you sawed a yardstick in half and plotted the inches read off the two halves. You’d also get the same kind of a plot (obviously) if you paired up measures of the same things from two different manufacturer’s inch rulers, or from two different brands of metersticks. And you could do the same kind of thing with ounces and grams, or degrees Fahrenheit and Celsius.

So here we are immersed in the boring-to-the-point-of-being-banal details of measurement. We take these alignments completely for granted, but they are not given to us for nothing. They are products of the huge investments we make in metrological standards. Metrology came of age in the early nineteenth century. Until then, weights and measures varied from market to market. Units with the same name might be different sizes, and units with different names might be the same size. As was so rightly celebrated on World Metrology Day (May 20), metric uniformity contributes hugely to the world economy by reducing transaction costs and by structuring representations of fair value.

We are in dire need of similar metrological systems for human, social, and natural capital. Health care reform, improved education systems, and environmental management will not come anywhere near realizing their full potentials until we establish, implement, and monitor metrological standards that bring intangible forms of capital to economic life.

But can we construct plots like Figure 1 from the numeric scores, ratings, and percentages we commonly assume to be measures? Figure 2 shows the kind of picture we get when we plot percentages against each other (scores and ratings behave in the same way, for reasons given below). These data might be from easy and hard halves of the same reading or math test, from agreeable and disagreeable ends of the same rating scale survey, or from different tests or surveys that happen to vary in their difficulty or agreeability. The Figure 2 data might also come from different situations in which some event or outcome occurs more frequently in one place than it does in another (we’ll go more into this in Part Two of this report).

Figure 2. Percents Correct or Agreement from Different Tests or Surveys

Figure 2. Percents Correct or Agreement from Different Tests or Surveys

In contrast with the linear relation obtained in the comparison of inches and centimeters, here we have a curve. Why must this relation necessarily be curved? It cannot be linear because both instruments limit their measurement ranges, and they set different limits. So, if someone scores a 0 on the easy instrument, they are highly likely to also score 0 on the instrument posing more difficult or disagreeable questions. Conversely, if someone scores 100 on the hard instrument, they are highly likely to also score 100 on the easy one.

But what is going to happen in the rest of the measurement range? By the definition of easy and hard, scores on the easy instrument will be higher than those on the hard one. And because the same measured amount is associated with different ranges in the easy and hard score distributions, the scores vary at different rates (Part Two will explore this phenomenon in more detail).

These kinds of numbers are called ordinal because they meaningfully convey information about rank order. They do not, however, stand for amounts that add up. We are, of course, completely free to treat these ordinal numbers however we want, in any kind of arithmetical or statistical comparison. Whether such comparisons are meaningful and useful is a completely different issue.

Figure 3 shows the Figure 2 data transformed. The mathematical transformation of the percentages produces what is known as a logit, so called because it is a log-odds unit, obtained as the natural logarithm of the response odds. (The response odds are the response probabilities–the original percentages of the maximum possible score–divided by one minus themselves.) This is the simplest possible way of estimating linear measures. Virtually no computer program providing these kinds of estimates would employ an algorithm this simple and potentially fallible.

Figure 3. Logit (Log-Odds Units) Estimates of the Figure 2 Data

Figure 3. Logit (Log-Odds Units) Estimates of the Figure 2 Data

Although the relationship shown in Figure 3 is not as precise as that shown in Figure 1, especially at the extremes, the values plotted fall far closer to the identity line than the values in Figure 2 do. Like Figure 1, Figure 3 shows that constant amounts of the thing measured exist irrespective of the particular number line they happen to be mapped onto.

What this means is that the two instruments could be designed so that the same numbers are read off of them when the same amounts are measured. We value numbers as much as we do because they are so completely transparent: 2+2=4 no matter what. But this transparency can be a liability when we assume that every unit amount is the same as all the others and they actually vary substantially. When different units stand for different amounts, confusion reigns. But we can reasonably hope and strive for great things as we bring human, social, and natural capital to life via universally uniform metrics traceable to reference standards.

A large literature on these methods exists and ought to be more widely read. For more information, see,, etc.

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And Here It Is: The Next Major Technological Breakthrough

May 29, 2009

How It Will Transform Your Business and Your Life

We’ve all witnessed an amazing series of events in our lifetimes, and, hopefully, we’ve learned some important lessons over the years. In business, we’ve come to see that innovation is rarely the work of one person. When the crowd has the right tools and puts its mind to the task, nothing can stop it. We’re accordingly also learning the real truth of the fact that any firm’s greatest resource is its people—there is no more effective source of new efficiencies and whole new directions. Concern for social responsibility is no longer the exclusive domain of activists, since everyone is now attuned to the susceptibility of markets to unrestrained greed. And there are increasingly good reasons for thinking that perhaps we can reverse ongoing major environmental debacles and orient our systems to profits that are sustainable over the long term.

And in our personal lives, we’ve learned the vital importance of access to learning opportunities across the lifespan, access to health care, and caring relationships. Whether we call it spiritual or not, life is hardly worth living without a sense of wonder at the very existence of the universe and all the strange things inhabiting it.

We’ve learned a few things, then. Perhaps foremost among them is that we are going to have to adapt to the changes we ourselves bring about. And given the pace of change and the plain need to do better, we don’t hear anyone repeating Lord Kelvin’s famous opinion, from the end of the nineteenth century, that pretty much everything that can be discovered has been discovered. (Though isn’t there someone at Microsoft who could top the classics “No one will ever need more than 640k memory—or more than one browser tab”?) With everything that’s happened in the 100 years or so since Kelvin’s remark, one of the big lessons that has been learned is a certain humility, at least in that regard.

Change is in the air, that’s for sure, even if it doesn’t seem that there is any one particular form of it. But in fact there is an important new technology coming on line. It isn’t really new. Viewed narrowly, it has been taking shape for over 80 years, even though its root mathematical principles go back to Plato (like so many do). And, at least in retrospect, this new technology’s major features may seem very humdrum and mundane, they are so everyday.

So just what is going on? Speaking in Abu Dhabi on Monday, May 25, Nobel economist Paul Krugman suggested that economic recovery could come about in the wake of a new major technological breakthrough, one of the size and scope of the IT revolution of the 1990s. Other factors cited by Krugman as candidates for turning things around included more investment by major corporations, and new climate change regulations and policies.

Industry-wide systems of metrological reference standards for human, social, and natural capital fit the bill. They are a new technological breakthrough on the scale of the initial IT revolution. They would also be a natural outgrowth of existing IT systems and an extension of existing global trade standards. Such systems would also require large investments from major corporations, and would facilitate highly significant moves on climate change.

In addition, stepping beyond the solutions suggested by Krugman, systematic and objective methods of measuring living capital would help meet the widely recognized need for socially responsible and sustainable business practices. Better measurement will play a vital role in reducing transaction costs and making human, social, and natural capital markets more efficient. It will also be essential to fostering new forms of innovation, as the shared standards and common product definitions made possible by advanced measurement systems enable people to think and act together collectively in common languages.

Striking advances have been made in measurement practice in recent years. It is easy to assume that the assignment of numbers to observations suffices as measurement, and that there have been no developments worthy of note in measurement theory or practice for decades. Nothing could be further from the truth. You don’t know the first thing about what you don’t know about measurement.

I came into the study and use of mathematically rigorous measurement and instrument calibration methods from the history and philosophy of science. The principles that make rulers, weight scales, clocks, and thermometers as meaningful, convenient and practical as they are, and that drive engineering practices in high tech, for instance, are pretty well understood. What’s more, those principles have been successfully applied to tests, rating scales, and assessments for decades, primarily in high stakes graduation, admissions, and certification/licensure testing. Increasingly these principles are finding their way into health care and business.

The general public doesn’t know much about all of this because the math is pretty intense, the software is hard to use, and we have an ingrained cultural prejudice that says all we have to do is come up with numbers of some kind, and–voila!– we have measurement. Nothing could be further from the truth.

My goal in all of this is to figure out how to put tools that work in the hands of the people who need them. You don’t need a PhD in thermodynamics to read a thermometer, so we ought to be able to calibrate similar instruments for other things we want to measure. And the way transparency and accountability demands are converging with economics and technology, I think the time is ripe for new ideas properly presented.

A quick way to see the point is to recognize that fair and just measures have to represent something that adds up the way the numbers do. Numbers don’t just automatically do that. We invest huge resources in crafting good instruments in the natural sciences, but we assume anyone at all can put together a measure using counts of right answers or sums of ratings or percents of the time some event occurs. But none of these are measures. Numbers certainly always add up in the same way, but whether they are meaningful or not is a question that is rarely asked. The numbers we often take as measures of outcomes or results or processes almost never stand for something that adds up the way everyone thinks they do.

So, yes, I know we need metrics that are manageable, understandable, and relevant. And I know how quickly people’s eyes glaze over in face of what they think are irrelevant technicalities. But eyes also tend to glaze over when something unexpected and completely different is offered. True originality is not easily categorized or recognized for what it is. And when something is fundamentally different from what people are used to, it can be rejected just because it is more trouble to to make the transition to a new system than it is to remain with the existing system, no matter how dysfunctional it is.

And boy is the current way of developing and deploying business metrics dysfunctional! Do you know that the difference between 1 percent and 2 percent can represent 4-8 times the difference between 49 percent and 50 percent? Did you know that sometimes a 15% difference can stand for as much as or even a lot more than a 39% difference? Did you know that three markedly different percentage values—differences that vary by more than a standard error or even five—might actually stand for the same measured amount?

In my 25 years of experience in measurement, people often turn out to not understand what they think they understand. And they then also turn out to be amazed at what they learn when they take the trouble to put some time and care into crafting an instrument that really measures what they’re after.

For instance, did you know that there are mathematical ways of reducing data volume that not only involve no loss of information but that actually increase the amount of actionable value? Given the way we are swimming in seas of data that do not usually mean what we think they mean, being able to experimentally make sure things add up properly at the same time we reduce the volume of numbers we have to deal with seems to me to be an eminently practical aid to understanding and manageability.

Did you know that different sets of indicators or items can measure in a common metric? Or that a large bank of items can be adaptively administered, with the instrument individually tailored and customized for each respondent, organization, or situation, all without compromising the comparability of the measures?

These are highly practical things to be able to do. Markets live and die on shared product definitions and shared metrics. Innovation almost never happens as a result of one person’s efforts; it is almost always a result of activities coordinated through a network structured by a common language of reference standards. We are very far from having the markets and levels of innovation we need in large part because the quality of measurement in so many business applications is so poor. But that is going to change in very short order as those most banal of subjects, measurement and metrological systems, catch fire.

World Metrology Day (May 20)

May 27, 2009

World Metrology Day, Science and Commerce
How to Reinvigorate the Economy via Better Measurement

An Open Letter to the President’s
Economic Recovery Advisory Board


William P. Fisher, Jr.
Living Capital Metrics
5252 Annunciation Street
New Orleans, LA 70115

“Measurements in Commerce: Metrology Underpinning Economic Development” is the name of the National Institute for Standards and Technology’s World Metrology Day educational event in Gaithersburg, MD, held on Wednesday, May 20. Similar events around the world celebrated the economic prosperity and scientific successes that have followed from the signing of the Metre Convention in 1875.

For those wondering what the noise is all about, there are two reasons why we need a World Metrology Day. The first one is what the speakers at the NIST educational event addressed. Despite the vitally important role measurement and technical standards play in the economy, we take them almost completely for granted. Their very invisibility indicates how well they are working, but also makes it important that the public be reminded about them from time to time.

The second reason why we need a World Metrology Day concerns the role measurement science can, ought, and ultimately must play in reinvigorating the economy, and in supporting green, socially responsible, and sustainable economic policies and practices. Better measurement is capable of enhancing the security of the existing economic pie, and in expanding both its size and the fairness with which it is divvied up. In order to understand how these expansions are coming about, we need to start from what metrology is and does in the first place.

Confidence in our rulers, weight scales, clocks, thermometers, volt meters, and so on—trust that they all read out the same value for the same amount measured—is what metrology gives us. As you might imagine, commerce and science were seriously impeded in those historical epochs when measures varied depending on who made them, who used them, or which instrument they were made with. Ensuring consistent price-value relationships, and the interoperability of various technologies, are highly significant ways in which metrological standards keep transaction costs low and lubricate the wheels of commerce.

The need for standardized product definitions makes metrology ubiquitous. Metrological standards are quite costly, as much as 20 percent of any nation’s GDP, making them much too expensive for any one business or industry to create for themselves. But those investments provide remarkably high returns, from 32% to over 400%, as shown by NIST studies. Small businesses benefit to an especially large degree from the efforts made by NIST and other standards groups around the world to ensure the smooth flow of products in global markets.

There is a human side to measurement, too. Beyond the market and the laboratory, fairness in measurement is a recurring theme in the Bible, the Torah, and the Q’uran, as well as in the Magna Carta and the constitutions of nations everywhere. The Golden Rule itself can be seen as demanding that the scales of justice be balanced in the hands of a judge blind to everything but the truth.

And so metrological standards not only provide cost-effective precision, they also embody our notions of fairness, justice, and right conduct. The French Revolution, for instance, very self-consciously understood the universal measures proclaimed in the metric system as symbolically representing the ideals of universal rights for all people.

These historical achievements provide us with a model for the future. How so? The current global crisis resounds with cries for accountability and transparency, with expanded human rights, social justice, and environmental quality. Activists and managers in every area, from education to health care to governance to philanthropy, deplore their metrics and wonder how to beg, buy, borrow, or steal better ones. Their needs are real, demand is huge, and, fortunately, the methods they need are readily available.

Demand for fair, universally uniform, comparable, and accessible measures of school, hospital, employment, community, and environmental quality sets the stage for a major expansion of the role of metrology and its effects on the economy. Standardized product definitions for tangible amounts of things sold by weight, volume, area, time, or kilowatts are essential to the efficiency and fairness of markets. They will be equally essential to the efficiency and fairness of human, social, and natural capital markets.

Some readers may at this point be wondering how measurement with the necessary mathematical rigor and scientific precision can be obtained for this purpose, if it can be obtained at all (see box, below). Although measurement in psychology and the social sciences is roundly disparaged by many unfamiliar with its technical achievements, it has come of age in recent decades. The wider world desperately needs to know more, both about the advances that have been made, and about what still needs to be done.

In a nutshell, tests, assessments, and surveys are routinely calibrated to be equivalent in principle with physical measures in their objectivity, mathematical rigor, practicality, and meaningfulness. The problem is not only that hardly anyone is aware this is being done; more importantly, even those doing the work are unaware of the need to create systems of metrological standards for each various form of human, social, and natural capital. The special value of being able to think together harmoniously, using instruments tuned to the same scale, is lost on those accustomed to dealing with one customer, student, or patient at a time, or with one test, survey, or data set at a time.

But being able to think together in a common language as consumers and producers is what makes a market efficient. Having different names for the same things, or the same names for different things, is confusing. When measuring units change in a variety of uncontrolled ways, communication is compromised and markets are bogged down in frictions that waste resources, add to costs, and can leave one or the other partner to a transaction feeling cheated.

Unfortunately, measures of the quality of schooling, health care, governance, environmental management, etc. almost always vary in uncontrolled ways. Assessment instruments are only rarely calibrated using the kinds of quality standards we take for granted when we weigh produce in the grocery store. And even when instruments are properly calibrated, and they increasingly are, they do not share a common metric.

In addition, because so few know that instruments can be calibrated and that they can be equated to a shared quantitative scale, we lack the systems, both vertical, within organizations, and horizontal, between them, through which the information might flow to each different place it is needed.

What we need today are

1. metrological systems designed to calibrate instruments, equate them, and maintain the equatings,

2. educational systems designed to inform researchers and students about the value of research designed to produce meaningful and stable measurement,

3. management systems designed to incorporate the metrics where they are needed, at every level and in every division, in production, quality improvement, accounting, marketing, human, social, and environmental resource management, governance, etc.; and

4. funding to support each of these areas of endeavor.

The funding is significant, both for the large amounts that will be needed, and for the quality of the investments to be made. Given the very large returns obtained from existing metrology systems, there will be intense interest in extending those systems to new domains. NIST plainly should have a new division focusing on measuring instruments and metrology systems for human, social, and natural capital. NIH, AHRQ, and other federal research arms should require all research proposals to address instrument calibration, how the resulting metrics will be maintained relative to reference standards, and how stakeholders’ various applications will employ it. Further down the road, new accounting standards will be needed for incorporating the new forms of capital into spreadsheets, and econometric models will include values for service products defined in common terms.

NIST’s World Metrology Day symposium emphasizes the the everyday and essential role that measurement science and standards play in virtually every economic transaction. New metrological horizons are upon us, however. The crisis we are currently experiencing is a prime opportunity for creating and investing in the infrastructure of new systems that will pay dividends for years to come.

Some may be suspicious of the claim that tests and surveys can measure with the same kind of objectivity as a clock or weight scale. Such suspicions are, however, easily overcome with a bit of history. Of particular interest are two electrical engineer/physicists turned psychologists and a mathematician, all of whom had close connections with the University of Chicago.

L. L. Thurstone was a former electrical engineer turned psychologist who became the first president of the Psychometric Society. Writing in 1928, while a Professor at the University of Chicago, Thurstone held that measurement was achieved only to the extent that an instrument behaving like a ruler could be calibrated. As Thurstone put it, if a ruler measured differently depending on whether it was a piece of paper or a rug that was being measured, then that instrument’s trustworthiness as a measuring device would be impaired. Thurstone, his colleagues, and his students made significant headway in constructing scales that lived up to this demanding criterion. His methods were deemed cumbersome by those less concerned with meaningfulness and science than with expeditious analytic productivity, however, so much of Thurstone’s best work was neglected as the years passed.

Further strides were made in the 1950s by Georg Rasch, a Danish mathematician who had studied with Ronald Fisher in London in 1934-5. Rasch was also strongly influenced by the Nobel economist, Ragnar Frisch, with whom he studied in Oslo. From Fisher, Rasch took an emphasis on statistical sufficiency, and from Frisch, the related understanding that generalizable results must be autonomous from the data representing them. The connections with Fisher and Frisch led Rasch to work with the Cowles Commission at the University of Chicago in 1947, where Rasch made the acquaintance of the statistician, Jimmy Savage. A few years later, Rasch showed decisively that, with the right test instrument and data, the reading ability of a child could be measured with the same kind of objectivity obtained in measuring her or his weight.

Rasch’s models have become widely used in high stakes and commercial testing globally, especially in advanced computerized examinations, largely due to the efforts of Benjamin D. Wright. Wright had worked under Nobel laureates Townes, Mulliken, and Feynman in a previous life as an electrical engineer and physicist. In 1960, as an Assistant Professor of Education at the University of Chicago, at the urging of his friend and colleague, Jimmy Savage, Wright hosted a seminar series given by Rasch. Wright felt that Rasch resolved some of his own dilemmas concerning the reconciliation of the scientific values he had learned in physics with the methods then popular in educational research. Wright went so far in adopting Rasch’s models as to develop improved methods for estimating their parameters, new statistics for evaluating data quality and instrument reliability, what was for many years the most advanced software for analyzing data, and professional societies and publications for sharing new contributions.

Toward the end of his career, Wright wrote that there is no methodological reason why measurement in education and psychology cannot be as stable, reproducible, and useful as measurement in physics. Over 50 years of experience with Rasch’s models, and 30 before that with Thurstone’s, provides evidence conclusively supporting Wright’s position.