Archive for the ‘capital’ Category

Excerpts and Notes from Goldberg’s “Billions of Drops…”

December 23, 2015

Goldberg, S. H. (2009). Billions of drops in millions of buckets: Why philanthropy doesn’t advance social progress. New York: Wiley.

p. 8:
Transaction costs: “…nonprofit financial markets are highly disorganized, with considerable duplication of effort, resource diversion, and processes that ‘take a fair amount of time to review grant applications and to make funding decisions’ [citing Harvard Business School Case No. 9-391-096, p. 7, Note on Starting a Nonprofit Venture, 11 Sept 1992]. It would be a major understatement to describe the resulting capital market as inefficient.”

A McKinsey study found that nonprofits spend 2.5 to 12 times more raising capital than for-profits do. When administrative costs are factored in, nonprofits spend 5.5 to 21.5 times more.

For-profit and nonprofit funding efforts contrasted on pages 8 and 9.

p. 10:
Balanced scorecard rating criteria

p. 11:
“Even at double-digit annual growth rates, it will take many years for social entrepreneurs and their funders to address even 10% of the populations in need.”

p. 12:
Exhibit 1.5 shows that the percentages of various needs served by leading social enterprises are barely drops in the respective buckets; they range from 0.07% to 3.30%.

pp. 14-16:
Nonprofit funding is not tied to performance. Even when a nonprofit makes the effort to show measured improvement in impact, it does little or nothing to change their funding picture. It appears that there is some kind of funding ceiling implicitly imposed by funders, since nonprofit growth and success seems to persuade capital sources that their work there is done. Mediocre and low performing nonprofits seem to be able to continue drawing funds indefinitely from sympathetic donors who don’t require evidence of effective use of their money.

p. 34:
“…meaningful reductions in poverty, illiteracy, violence, and hopelessness will require a fundamental restructuring of nonprofit capital markets. Such a restructuring would need to make it much easier for philanthropists of all stripes–large and small, public and private, institutional and individual–to fund nonprofit organizations that maximize social impact.”

p. 54:
Exhibit 2.3 is a chart showing that fewer people rose from poverty, and more remained in it or fell deeper into it, in the period of 1988-98 compared with 1969-1979.

pp. 70-71:
Kotter’s (1996) change cycle.

p. 75:
McKinsey’s seven elements of nonprofit capacity and capacity assessment grid.

pp. 94-95:
Exhibits 3.1 and 3.2 contrast the way financial markets reward for-profit performance with the way nonprofit markets reward fund raising efforts.

Financial markets
1. Market aggregates and disseminates standardized data
2. Analysts publish rigorous research reports
3. Investors proactively search for strong performers
4. Investors penalize weak performers
5. Market promotes performance
6. Strong performers grow

Nonprofit markets
1. Social performance is difficult to measure
2. NPOs don’t have resources or expertise to report results
3. Investors can’t get reliable or standardized results data
4. Strong and weak NPOs spend 40 to 60% of time fundraising
5. Market promotes fundraising
6. Investors can’t fund performance; NPOs can’t scale

p. 95:
“…nonprofits can’t possibly raise enough money to achieve transformative social impact within the constraints of the existing fundraising system. I submit that significant social progress cannot be achieved without what I’m going to call ‘third-stage funding,’ that is, funding that doesn’t suffer from disabling fragmentation. The existing nonprofit capital market is not capable of [p. 97] providing third-stage funding. Such funding can arise only when investors are sufficiently well informed to make big bets at understandable and manageable levels of risk. Existing nonprofit capital markets neither provide investors with the kinds of information needed–actionable information about nonprofit performance–nor provide the kinds of intermediation–active oversight by knowledgeable professionals–needed to mitigate risk. Absent third-stage funding, nonprofit capital will remain irreducibly fragmented, preventing the marshaling of resources that nonprofit organizations need to make meaningful and enduring progress against $100 million problems.”

pp. 99-114:
Text and diagrams on innovation, market adoption, transformative impact.

p. 140:
Exhibit 4.2: Capital distribution of nonprofits, highlighting mid-caps

pages 192-3 make the case for the difference between a regular market and the current state of philanthropic, social capital markets.

p. 192:
“So financial markets provide information investors can use to compare alternative investment opportunities based on their performance, and they provide a dynamic mechanism for moving money away from weak performers and toward strong performers. Just as water seeks its own level, markets continuously recalibrate prices until they achieve a roughly optimal equilibrium at which most companies receive the ‘right’ amount of investment. In this way, good companies thrive and bad ones improve or die.
“The social sector should work the same way. .. But philanthropic capital doesn’t flow toward effective nonprofits and away from ineffective nonprofits for a simple reason: contributors can’t tell the difference between the two. That is, philanthropists just don’t [p. 193] know what various nonprofits actually accomplish. Instead, they only know what nonprofits are trying to accomplish, and they only know that based on what the nonprofits themselves tell them.”

p. 193:
“The signs that the lack of social progress is linked to capital market dysfunctions are unmistakable: fundraising remains the number-one [p. 194] challenge of the sector despite the fact that nonprofit leaders divert some 40 to 60% of their time from productive work to chasing after money; donations raised are almost always too small, too short, and too restricted to enhance productive capacity; most mid-caps are ensnared in the ‘social entrepreneur’s trap’ of focusing on today and neglecting tomorrow; and so on. So any meaningful progress we could make in the direction of helping the nonprofit capital market allocate funds as effectively as the private capital market does could translate into tremendous advances in extending social and economic opportunity.
“Indeed, enhancing nonprofit capital allocation is likely to improve people’s lives much more than, say, further increasing the total amount of donations. Why? Because capital allocation has a multiplier effect.”

“If we want to materially improve the performance and increase the impact of the nonprofit sector, we need to understand what’s preventing [p. 195] it from doing a better job of allocating philanthropic capital. And figuring out why nonprofit capital markets don’t work very well requires us to understand why the financial markets do such a better job.”

p. 197:
“When all is said and done, securities prices are nothing more than convenient approximations that market participants accept as a way of simplifying their economic interactions, with a full understanding that market prices are useful even when they are way off the mark, as they so often are. In fact, that’s the whole point of markets: to aggregate the imperfect and incomplete knowledge held by vast numbers of traders about much various securities are worth and still make allocation choices that are better than we could without markets.
“Philanthropists face precisely the same problem: how to make better use of limited information to maximize output, in this case, social impact. Considering the dearth of useful tools available to donors today, the solution doesn’t have to be perfect or even all that good, at least at first. It just needs to improve the status quo and get better over time.
“Much of the solution, I believe, lies in finding useful adaptations of market mechanisms that will mitigate the effects of the same lack of reliable and comprehensive information about social sector performance. I would even go so far as to say that social enterprises can’t hope to realize their ‘one day, all children’ visions without a funding allociation system that acts more like a market.
“We can, and indeed do, make incremental improvements in nonprofit funding without market mechanisms. But without markets, I don’t see how we can fix the fragmentation problem or produce transformative social impact, such as ensuring that every child in America has a good education. The problems we face are too big and have too many moving parts to ignore the self-organizing dynamics of market economics. As Thomas Friedman said about the need to impose a carbon tax at a time of falling oil prices, ‘I’ve wracked my brain trying to think of ways to retool America around clean-power technologies without a price signal–i.e., a tax–and there are no effective ones.”

p. 199:
“Prices enable financial markets to work the way nonprofit capital markets should–by sending informative signals about the most effective organizations so that money will flow to them naturally..”

p. 200:
[Quotes Kurtzman citing De Soto on the mystery of capital. Also see p. 209, below.]
“‘Solve the mystery of capital and you solve many seemingly intractable problems along with it.'”
[That’s from page 69 in Kurtzman, 2002.]

p. 201:
[Goldberg says he’s quoting Daniel Yankelovich here, but the footnote does not appear to have anything to do with this quote:]
“‘The first step is to measure what can easily be measured. The second is to disregard what can’t be measured, or give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can’t be measured easily isn’t very important. This is blindness. The fourth step is to say that what can’t be easily measured really doesn’t exist. This is suicide.'”

Goldberg gives example here of $10,000 invested witha a 10% increase in value, compared with $10,000 put into a nonprofit. “But if the nonprofit makes good use of the money and, let’s say, brings the reading scores of 10 elementary school students up from below grade level to grade level, we can’t say how much my initial investment is ‘worth’ now. I could make the argument that the value has increased because the students have received a demonstrated educational benefit that is valuable to them. Since that’s the reason I made the donation, the achievement of higher scores must have value to me, as well.”

p. 202:
Goldberg wonders whether donations to nonprofits would be better conceived as purchases than investments.

p. 207:
Goldberg quotes Jon Gertner from the March 9, 2008, issue of the New York Times Magazine devoted to philanthropy:

“‘Why shouldn’t the world’s smartest capitalists be able to figure out more effective ways to give out money now? And why shouldn’t they want to make sure their philanthropy has significant social impact? If they can measure impact, couldn’t they get past the resistance that [Warren] Buffet highlighted and finally separate what works from what doesn’t?'”

p. 208:
“Once we abandon the false notions that financial markets are precision instruments for measuring unambiguous phenomena, and that the business and nonproft sectors are based in mutually exclusive principles of value, we can deconstruct the true nature of the problems we need to address and adapt market-like mechanisms that are suited to the particulars of the social sector.
“All of this is a long way (okay, a very long way) of saying that even ordinal rankings of nonprofit investments can have tremendous value in choosing among competing donation opportunities, especially when the choices are so numerous and varied. If I’m a social investor, I’d really like to know which nonprofits are likely to produce ‘more’ impact and which ones are likely to produce ‘less.'”

“It isn’t necessary to replicate the complex working of the modern stock markets to fashion an intelligent and useful nonprofit capital allocation mechanism. All we’re looking for is some kind of functional indication that would (1) isolate promising nonprofit investments from among the confusing swarm of too many seemingly worthy social-purpose organizations and (2) roughly differentiate among them based on the likelihood of ‘more’ or ‘less’ impact. This is what I meant earlier by increasing [p. 209] signals and decreasing noise.”

p. 209:
Goldberg apparently didn’t read De Soto, as he says that the mystery of capital is posed by Kurtzman and says it is solved via the collective intelligence and wisdom of crowds. This completely misses the point of the crucial value that transparent representations of structural invariance hold in market functionality. Goldberg is apparently offering a loose kind of market for which there is an aggregate index of stocks for nonprofits that are built up from their various ordinal performance measures. I think I find a better way in my work, building more closely from De Soto (Fisher, 2002, 2003, 2005, 2007, 2009a, 2009b).

p. 231:
Goldberg quotes Harvard’s Allen Grossman (1999) on the cost-benefit boundaries of more effective nonprofit capital allocation:

“‘Is there a significant downside risk in restructuring some portion of the philanthropic capital markets to test the effectiveness of performance driven philanthropy? The short answer is, ‘No.’ The current reality is that most broad-based solutions to social problems have eluded the conventional and fragmented approaches to philanthropy. It is hard to imagine that experiments to change the system to a more performance driven and rational market would negatively impact the effectiveness of the current funding flows–and could have dramatic upside potential.'”

p. 232:
Quotes Douglas Hubbard’s How to Measure Anything book that Stenner endorsed, and Linacre and I didn’t.

p. 233:
Cites Stevens on the four levels of measurement and uses it to justify his position concerning ordinal rankings, recognizing that “we can’t add or subtract ordinals.”

pp. 233-5:
Justifies ordinal measures via example of Google’s PageRank algorithm. [I could connect from here using Mary Garner’s (2009) comparison of PageRank with Rasch.]

p. 236:
Goldberg tries to justify the use of ordinal measures by citing their widespread use in social science and health care. He conveniently ignores the fact that virtually all of the same problems and criticisms that apply to philanthropic capital markets also apply in these areas. In not grasping the fundamental value of De Soto’s concept of transferable and transparent representations, and in knowing nothing of Rasch measurement, he was unable to properly evaluate to potential of ordinal data’s role in the formation of philanthropic capital markets. Ordinal measures aren’t just not good enough, they represent a dangerous diversion of resources that will be put into systems that take on lives of their own, creating a new layer of dysfunctional relationships that will be hard to overcome.

p. 261 [Goldberg shows here his complete ignorance about measurement. He is apparently totally unaware of the work that is in fact most relevant to his cause, going back to Thurstone in 1920s, Rasch in the 1950s-1970s, and Wright in the 1960s to 2000. Both of the problems he identifies have long since been solved in theory and in practice in a wide range of domains in education, psychology, health care, etc.]:
“Having first studied performance evaluation some 30 years ago, I feel confident in saying that all the foundational work has been done. There won’t be a ‘eureka!’ breakthrough where someone finally figures out the one true way to guage nonprofit effectiveness.
“Indeed, I would venture to say that we know virtually everything there is to know about measuring the performance of nonprofit organizations with only two exceptions: (1) How can we compare nonprofits with different missions or approaches, and (2) how can we make actionable performance assessments common practice for growth-ready mid-caps and readily available to all prospective donors?”

p. 263:
“Why would a social entrepreneur divert limited resources to impact assessment if there were no prospects it would increase funding? How could an investor who wanted to maximize the impact of her giving possibly put more golden eggs in fewer impact-producing baskets if she had no way to distinguish one basket from another? The result: there’s no performance data to attract growth capital, and there’s no growth capital to induce performance measurement. Until we fix that Catch-22, performance evaluation will not become an integral part of social enterprise.”

pp. 264-5:
Long quotation from Ken Berger at Charity Navigator on their ongoing efforts at developing an outcome measurement system. [wpf, 8 Nov 2009: I read the passage quoted by Goldberg in Berger’s blog when it came out and have been watching and waiting ever since for the new system. wpf, 8 Feb 2012: The new system has been online for some time but still does not include anything on impacts or outcomes. It has expanded from a sole focus on financials to also include accountability and transparency. But it does not yet address Goldberg’s concerns as there still is no way to tell what works from what doesn’t.]

p. 265:
“The failure of the social sector to coordinate independent assets and create a whole that exceeds the sum of its parts results from an absence of.. platform leadership’: ‘the ability of a company to drive innovation around a particular platform technology at the broad industry level.’ The object is to multiply value by working together: ‘the more people who use the platform products, the more incentives there are for complement producers to introduce more complementary products, causing a virtuous cycle.'” [Quotes here from Cusumano & Gawer (2002). The concept of platform leadership speaks directly to the system of issues raised by Miller & O’Leary (2007) that must be addressed to form effective HSN capital markets.]

p. 266:
“…the nonprofit sector has a great deal of both money and innovation, but too little available information about too many organizations. The result is capital fragmentation that squelches growth. None of the stakeholders has enough horsepower on its own to impose order on this chaos, but some kind of realignment could release all of that pent-up potential energy. While command-and-control authority is neither feasible nor desirable, the conditions are ripe for platform leadership.”

“It is doubtful that the IMPEX could amass all of the resources internally needed to build and grow a virtual nonprofit stock market that could connect large numbers of growth-capital investors with large numbers of [p. 267] growth-ready mid-caps. But it might be able to convene a powerful coalition of complementary actors that could achieve a critical mass of support for performance-based philanthropy. The challenge would be to develop an organization focused on filling the gaps rather than encroaching on the turf of established firms whose participation and innovation would be required to build a platform for nurturing growth of social enterprise..”

p. 268-9:
Intermediated nonprofit capital market shifts fundraising burden from grantees to intermediaries.

p. 271:
“The surging growth of national donor-advised funds, which simplify and reduce the transaction costs of methodical giving, exemplifies the kind of financial innovation that is poised to leverage market-based investment guidance.” [President of Schwab Charitable quoted as wanting to make charitable giving information- and results-driven.]

p. 272:
Rating agencies and organizations: Charity Navigator, Guidestar, Wise Giving Alliance.
Online donor rankings: GlobalGiving, GreatNonprofits, SocialMarkets
Evaluation consultants: Mathematica

Google’s mission statement: “to organize the world’s information and make it universally accessible and useful.”

p. 273:
Exhibit 9.4 Impact Index Whole Product
Image of stakeholders circling IMPEX:
Trading engine
Listed nonprofits
Data producers and aggregators
Trading community
Researchers and analysts
Investors and advisors
Government and business supporters

p. 275:
“That’s the starting point for replication [of social innovations that work]: finding and funding; matching money with performance.”

[WPF bottom line: Because Goldberg misses De Soto’s point about transparent representations resolving the mystery of capital, he is unable to see his way toward making the nonprofit capital markets function more like financial capital markets, with the difference being the focus on the growth of human, social, and natural capital. Though Goldberg intuits good points about the wisdom of crowds, he doesn’t know enough about the flaws of ordinal measurement relative to interval measurement, or about the relatively easy access to interval measures that can be had, to do the job.]

References

Cusumano, M. A., & Gawer, A. (2002, Spring). The elements of platform leadership. MIT Sloan Management Review, 43(3), 58.

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

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). Bringing human, social, and natural capital to life: Practical consequences and opportunities. In M. Wilson, K. Draney, N. Brown & B. Duckor (Eds.), Advances in Rasch Measurement, Vol. Two (p. in press [http://www.livingcapitalmetrics.com/images/BringingHSN_FisherARMII.pdf]). Maple Grove, MN: JAM Press.

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

Garner, M. (2009, Autumn). Google’s PageRank algorithm and the Rasch measurement model. Rasch Measurement Transactions, 23(2), 1201-2 [http://www.rasch.org/rmt/rmt232.pdf].

Grossman, A. (1999). Philanthropic social capital markets: Performance driven philanthropy (Social Enterprise Series 12 No. 00-002). Harvard Business School Working Paper.

Kotter, J. (1996). Leading change. Cambridge, Massachusetts: Harvard Business School Press.

Kurtzman, J. (2002). How the markets really work. New York: Crown Business.

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

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A truly ambitious plan to tackle climate change 

December 3, 2015

A recent story in the NY Times asks just what a truly ambitious plan to tackle climate change would look like. Pledges of emissions cuts being made in Paris this month are projected to fall short of what is needed to solve the problem of climate change. Calls for mass mobilization on the scale of the U.S.’s entry into WWII are met with skepticism at the same time that leaders are signing on for stronger terms in the Paris agreement than their countries have agreed to.

One crucial assumption is made across the full range of the proposals for more stringent standards and innovative technologies. That assumption is that solving the problem of climate change is a matter of marshaling the will to get the job done. On the face of it, of course, it seems inane to consider something as important as will power to be part of the problem. If people don’t want to do something, how could it possibly ever get done?

But as I’ve pointed out in a number of previous posts in this blog, complex problems sometimes cannot be solved from within the conceptual framework that engendered them. We are in this situation in large part because our overall relation to the earth is based on assuming it to be a bottomless well of resources, with the only limitation being the creativity we bring to bear in tapping those resources. Though many of us, perhaps a majority, are seriously committed to reconceiving our relation to the earth in sustainable terms, practical results are nearly impossible to produce within the existing institutional framework. Our economic, legal, accounting, education, etc. systems are all set up to support a consumer ethos that hobbles and undercuts almost all efforts intended to support an alternative sustainability ethos. It is both ironic and counterproductive to formulate solutions to the problem of climate change without first changing the institutional background assumptions informing the rules, roles and responsibilities through which we conceptualize and implement those solutions.

Insight into this problem is provided by recent work on standards for sustainability accounting. It shows that, by definition, efforts targeting change in economic externalities like environmental concerns cannot be scaled up in ways that are needed. This happens simply because balancing mission and margin demands maintenance of the bottom line. Giving away the business in the name of saving the planet might be a noble gesture but it is the opposite of sustainable and more importantly does not provide a viable model for the future.

So how do we model a new kind of bottom line that balances mission and margin in a new way? A way in which institutional rules, roles and responsibilities are themselves configured into the sustainable ecological relations we need? A way in which means and ends are unified? How do we become the change we want to see? How can we mobilize an international mass movement focused on doing what needs to be done to solve the problem of climate change? What possibilities do we have for catalyzing the increasingly saturated solution of global discontent and desire for a new relation to the earth? Can natural social processes of leaderless self organizing systems be seeded and guided to fruition? What would that seeding and guidance look like?

For proposed answers to these questions and more on what a model of a truly ambitious plan to tackle climate change might look like, see other posts in this blog here, here, here, and here.

With Reich in spirit, but with a different sense of the problem and its solution

October 4, 2015

In today’s editorial in the San Francisco Chronicle, Robert Reich seeks some way of defining a solution to the pressing problems of how globalization and technological changes have made American workers less competitive. He rightly says that “reversing the scourge of widening inequality requires reversing the upward distributions [of income] within the rules of the market, and giving average people the bargaining power they need to get a larger share of the gains from growth.”

But Reich then says that the answer to this problem lies in politics, not economics. As I’ve pointed out before in this blog, focusing on marshaling political will is part of the problem, not part of the solution. Historically, politicians do not lead, they follow. As is demonstrated across events as diverse as the Arab Spring and the Preemption Act of 1841, mass movements of people have repeatedly demanded ways of cutting through the Gordian knots of injustice. And just as the political “leadership” across the Middle East and in the early U.S. dragged its feet, obstructed, and violently opposed change until it was already well underway, so, too, will that pattern repeat itself again in the current situation of inequitable income distribution.

The crux of the problem is that no one can give average people anything, not freedom (contra Dylan’s line in Blowin’ in the Wind about “allowing” people to be free) and certainly not a larger share of the gains from growth. As the old saying goes, you can lead a horse to water, but you can’t make it drink. People have to take what’s theirs. They have to want it, they have to struggle for it, and they have to pay for it, or they cannot own it and it will never be worth anything to them.

It is well known that a lack of individual property rights doomed communism and socialism because when everything is owned collectively by everyone, no one takes responsibility for it. The profit motive has the capacity to drive people to change things. The problem is not in profit itself. If birds and bees and trees and grasses did not profit from the sun, soil, and rain, there would be no life. The problem is in finding how to get a functional, self-sustaining economic ecology off the ground, not in unrealistically trying to manipulate and micromanage every detail.

The fundamental relevant characteristic of the profits being made today from intellectual property rights is that our individual rights to our own human and social capital are counter-productively restricted and undeveloped. How can it be that no one has any idea how much literacy or health capital they have, or what it is worth?! We have a metric system that tells us how much real estate and manufactured capital we own, and we can price it. But despite the well-established scientific facts of decades of measurement science research and practice, none of us can say, “I own x number of shares of stock in intellectual, literacy, or community capital, that have a value of x dollars in today’s market.” We desperately need an Intangible Assets Metric System, and the market rules, roles, and responsibilities that will make it impossible to make a profit while destroying human, social, and natural capital.

In this vein, what Reich gets absolutely correct is hidden inside his phrase, “within the rules of the market.” As I’ve so often repeated in this blog, capitalism is not inherently evil; it is, rather, unfinished. The real evil is in prolonging the time it takes to complete it. As was so eloquently stated by Miller and O’Leary (2007, p. 710):

“Markets are not spontaneously generated by the exchange activity of buyers and sellers. Rather, skilled actors produce institutional arrangements, the rules, roles and relationships that make market exchange possible. The institutions define the market, rather than the reverse.”

We have failed to set up the institutional arrangements needed to define human, social, and natural capital markets. The problem is that we cannot properly manage three of the four major forms of capital (human, social, and natural, with the fourth being manufactured/property) because we do not measure them in a common language built into scientifically, economically, legally and financially accountable titles, deeds, and other instruments.

And so, to repeat another one of my ad nauseum broken record nostrums, the problem is the problem. As long as we keep defining problems in the way we always have, as matters of marshalling political will, we will inadvertently find ourselves contributing more to prolonging tragic and needless human suffering, social discontent, and environmental degradation.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-734.

Living Capital Metrics for Financial and Sustainability Accounting Standards

May 1, 2015

I was very happy a few days ago to come across Jane Gleeson-White’s new book, Six Capitals, or Can Accountants Save the Planet? Rethinking Capitalism for the 21st Century. The special value for me in this book comes in the form of an accessible update on what’s been going on in the world of financial accounting standards. Happily, there’s been a lot of activity (check out, for instance, Amato & White, 2013; Rogers & White, 2015). Less fortunately, the activity seems to be continuing to occur in the same measurement vacuum it always has, despite my efforts in this blog to broaden the conversation to include rigorous measurement theory and practice.

But to back up a bit, recent events around sustainability metric standards don’t seem to be connected to previous controversies around financial standards and economic modeling, which were more academically oriented to problems of defining and expressing value. Gleeson-White doesn’t cite any of the extensive literature in those areas (for instance, Anielski, 2007; Baxter, 1979; Economist, 2010; Ekins, 1992, 1999; Ekins, Dresner, & Dahlstrom, 2008; Ekins, Hillman, & Hutchins, 1992; Ekins & Voituriez, 2009; Fisher, 2009b, 2009c, 2011; Young & Williams, 2010). Valuation is still a problem, of course, as is the analogy between accounting standards and scientific standards (Baxter, 1979). But much of the sensitivity of the older academic debate over accounting standards seems to have been lost in the mad, though well-intentioned, rush to devise metrics for the traditionally externalized nontraditional forms of capital.

Before addressing the thousands of metrics in circulation and the science that needs to be brought to bear on them (the ongoing theme of posts in this blog), some attention to terminology is important. Gleeson-White refers to six capitals (manufactured, liquid, intellectual, human, social, and natural), in contrast with Ekins (1992; Ekins, et al., 2008), who describes four (manufactured, human, social, and natural). Gleeson-White’s liquid capital is cash money, which can be invested in capital (a means of producing value via ongoing services) and which can be extracted as a return on capital, but is not itself capital, as is shown by the repeated historical experience in many countries of printing money without stimulating economic growth and producing value. Of her remaining five forms of capital, intellectual capital is a form of social capital that can satisfactorily be categorized alongside the other forms of organization-level properties and systems involving credibility and trust.

On pages 209-227, Gleeson-White takes up questions relevant to the measurement and information quality topics of this blog. The context here is informed by the International Integrated Reporting Council’s (IIRC) December 2013 framework for accounting reports integrating all forms of capital (Amato & White, 2013), and by related efforts of the Sustainability Accounting Standards Board (SASB) (Rogers & White, 2015). Following the IIRC, Gleeson-White asserts that

“Not all the new capitals can be quantified, yet or perhaps ever–for example, intellectual, human and social capital, much of natural capital–and so integrated reports are not expected to provide quantitative measures of each of the capitals.”

Of course, this opinion flies in the face of established evidence and theory accepted by both metrologists (weights and measures standards engineers and physicists) and psychometricians as to the viability of rigorous measurement standards for the outcomes of education, health care, social services, natural resource management, etc. (Fisher, 2009b, 2011, 2012a, 2012b; Fisher & Stenner, 2011a, 2013, 2015; Fisher & Wilson, 2015; Mari & Wilson, 2013; Pendrill, 2014; Pendrill & Fisher, 2013, 2015; Wilson, 2013; Wilson, Mari, Maul, & Torres Irribarra, 2015). Pendrill (2014, p. 26), an engineer, physicist, and past president of the European Association of National Metrology Institutes, for instance, states that “The Rasch approach…is not simply a mathematical or statistical approach, but instead [is] a specifically metrological approach to human-based measurement.” As is repeatedly shown in this blog, access to scientific measures sets the stage for a dramatic transformation of the potential for succeeding in the goal of rethinking capitalism.

Next, Gleeson-White’s references to several of the six capitals as the “living” capitals (p. 193) is a literal reference to the fact that human, social, and natural capital are all carried by people, organizations/communities, and ecosystems. The distinction between dead and living capital elaborated by De Soto (2000) and Fisher (2002, 2007, 2010b, 2011), which involves making any form of capital fungible by representing it in abstract forms negotiable in banks and courts of law, is not taken into account, though this would seem to be a basic requirement that must be fulfilled before the rethinking of capitalism could said to have been accomplished.

Gleeson-White raises the pointed question as to exactly how integrated reporting is supposed to provoke positive growth in the nontraditional forms of capital. The concept of an economic framework integrating all forms of capital relative to the profit motive, as described in Ekins’ work, for instance, and as is elaborated elsewhere in this blog, seems just over the horizon, though repeated mention is made of natural capitalism (Hawken, Lovins, & Lovins, 1999). The posing of the questions provided by Gleeson-White (pp. 216-217) is priceless, however:

“…given integrated reporting’s purported promise to contribute to sustainable development by encouraging more efficient resource allocation, how might it actually achieve this for natural and social capitals on their own terms? It seems integrated reporting does nothing to address a larger question of resource allocation….”

“To me the fact that integrated reporting cannot address such questions suggests that as with the example of human capital, its promise to foster efficient resource allocation pertains only to financial capital and not to the other capitals. If we accept that the only way to save our societies and planet is to reconceive them in terms of capital, surely the efficient valuing and allocation of all six capitals must lie at the heart of any economics and accounting for the planet’s scarce resources in the twenty-first century.
“There is a logical inconsistency here: integrated reporting might be the beginning of a new accounting paradigm, but for the moment it is being practiced by an old-paradigm corporation: essentially, one obliged to make a return on financial capital at the cost of the other capitals.”

The goal requires all forms of capital to be integrated into the financial bottom line. Where accounting for manufactured capital alone burns living capital resources for profit, a comprehensive capital accounting framework defines profit in terms of reduced waste. This is a powerful basis for economics, as waste is the common root cause of human suffering, social discontent and environmental degradation (Hawken, Lovins, & Lovins, 1999).

Multiple bottom lines are counter-productive, as they allow managers the option of choosing which stakeholder group to satisfy, often at the expense of the financial viability of the firm (Jensen, 2001; Fisher, 2010a). Economic sustainability requires that profits be legally, morally, and scientifically contingent on a balance of powers distributed across all forms of capital. Though the devil will no doubt lurk in the details, there is increasing evidence that such a balance of powers can be negotiated.

A key point here not brought up by Gleeson-White concerns the fact that markets are not created by exchange activity, but rather by institutionalized rules, roles, and responsibilities (Miller & O’Leary, 2007) codified in laws, mores, technologies, and expectations. Translating historical market-making activities as they have played out relative to manufactured capital in the new domains of human, social, and natural capital faces a number of significant challenges, adapting to a new way of thinking about tests, assessments, and surveys foremost among them (Fisher & Stenner, 2011b).

One of the most important contributions advanced measurement theory and practice (Rasch, 1960; Wright, 1977; Andrich, 1988, 2004; Fisher & Wright, 1994; Wright & Stone, 1999; Bond & Fox, 2007; Wilson, 2005; Engelhard, 2012; Stenner, Fisher, Stone, & Burdick, 2013) can make to the process of rethinking capitalism involves the sorting out of the myriad metrics that have erupted in the last several years. Gleeson-White (p. 223) reports, for instance, that the Bloomberg financial information network now has over 750 ESG (Environmental, Social, Governance) data fields, which were extracted from reports provided by over 5,000 companies in 52 countries.  Similarly, Rogers and White (2015) say that

“…today there are more than 100 organizations offering more than 400 corporate sustainability ratings products that assess some 50,000 companies on more than 8,000 metrics of environmental, social and governance (ESG) performance.”

As is also the case with the UN Millennium Development Goals (Fisher, 2011b), the typical use of these metrics as single-item “quantities” is based in counts of relevant events. This procedure misses the basic point that counts of concrete things in the world are not measures. Is it not obvious that I can have ten rocks to your two, and you can still have more rock than I do? The same thing applies to any kind of performance ratings, survey responses, or test scores. We assign the same numeric increase to every addition of one more count, but hardly anyone experimentally tests the hypothesis that the counts all work together to measure the same thing. Those who think there’s no need for precision science in this context are ignoring the decades of successful and widespread technical work in this area, at their own risk.

The repetition of history here is fascinating. As Ashworth (2004, p. 1,314) put it, historically, “The requirements of increased trade and the fiscal demands of the state fuelled the march toward a regular form of metrology.” For instance, in 1875 it was noted that “the existence of quantitative correlations between the various forms of energy, imposes upon men of science the duty of bringing all kinds of physical quantity to one common scale of comparison” (Everett, 1875, p. 9). The moral and economic  value of common scales was recognized during the French revolution, when, Alder (2002, p. 32) documents, it was asked:

“Ought not a single nation have a uniform set of measures, just as a soldier fought for a single patrie? Had not the Revolution promised equality and fraternity, not just for France, but for all the people of the world? By the same token, should not all of the world’s people use a single set of weights and measures to encourage peaceable commerce, mutual understanding, and the exchange of knowledge? That was the purpose of measuring the world.”

The value of rigorously measuring human, social and natural capital includes meaningfully integrating qualitative substance with quantitative convenience, reduced data volume, augmenting measures with uncertainty and consistency indexes, and the capacity to take missing data into account (making possible instrument equating, item banking, etc.)  In contrast with the usual methods, rigorous science demands that experiments determine which indicators cohere to measure the same thing by repeatedly giving the same values across samples, over time and space, and across subsets of indicators. Beyond such data-based results, advanced theory makes it possible to arrive at explanatory, predictive methods that add a whole new layer of efficiency to the generation of indicators (de Boeck & Wilson, 2004; Stenner, et al., 2013).

Finally, Gleeson-White (pp. 220-221) reports that “In July 2011, the SASB [Sustainability Accounting Standards Board] was launched in the United States to create standardized measures for the new capitals.” “Founded by environmental engineer and sustainability expert Jean Rogers in San Francisco, SASB is creating a full set of industry-specific standards for sustainability accounting, with the aim of making this information more consistent and comparable.” As of May 2014, the SASB vice chair is Mary Schapiro, former SEC chair, and the chairman of SASB is Michael Bloomfield, former mayor of NYC and founder of the financial information empire. The “SASB is developing nonfinancial standards for eighty-nine industries grouped in ten different sectors and aims to have completed this grueling task by February 2015. It is releasing each set of metrics as they are completed.”

Like the SASB and other groups, Gleeson-White (p. 222) reports, Bloomberg

“aims to use its metrics to start ‘standardizing the discourse around sustainability, so we’re all talking about the same things in the same way,’ as Bloomberg’s senior sustainability strategist Andrew Park put it. What companies ‘desperately want,’ he says, is ‘a legitimate voice’ to tell them: ‘This is what you need to do. You exist in this particular sector. Here are the metrics that you need to be reporting out on. So SASB will provide that. And we think that’s important, because that will help clean up the metrics that ultimately the finance community will start using.’
“Bloomberg wants to price environmental, social and governance externalities to legitimize them in the eyes of financial capital.”

Gleeson-White (p. 225) continues, saying

“Bloomberg wants to do more generally what Trucost did for Puma’s natural capital inputs: create standardized measures for the new capitals–such as ecosystem services and social impacts–so that this information can be aggregated and used by investors. Park and Ravenel call the failure to value clean air, water, stable coastlines and other environmental goods ‘as much a failure to measure as it is a market failure per se–one that could be addressed in part by providing these ‘unpriced’ resources with quantitative parameters that would enable their incorporation into market mechanisms. Such mechanisms could then appropriately ‘regulate’ the consumption of those resources.'”

Integrating well-measured living capitals into the context of appropriately configured institutional rules, roles, and responsibilities for efficient markets (Fisher, 2010b) should indeed involve a capacity to price these resources quantitatively, though this capacity alone would likely prove insufficient to the task of creating the markets (Miller & O’Leary, 2007; Williamson, 1981, 1991, 2005). Rasch’s (1960, pp. 110-115) deliberate patterning of his measurement models on the form of Maxwell’s equations for Newton’s Second Law provides a mathematical basis for connecting psychometrics with both geometry and natural laws, as well as with the law of supply and demand (Fisher, 2010c, 2015; Fisher & Stenner, 2013a).

This perspective on measurement is informed by an unmodern or amodern, post-positivist philosophy (Dewey, 2012; Latour, 1990, 1993), as opposed to a modern and positivist, or postmodern and anti-positivist, philosophy (Galison, 1997). The essential difference is that neither a universalist nor a relativist perspective is necessary to the adoption of practices of traceability to metrological standards. Rather, focusing on local, situated, human relationships, as described by Wilson (2004) in education, for instance, offers a way of resolving the false dilemma of that dichotomous contrast. As Golinski (2012, p. 35) puts it, “Practices of translation, replication, and metrology have taken the place of the universality that used to be assumed as an attribute of singular science.” Haraway (1996, pp. 439-440) harmonizes, saying “…embedded relationality is the prophylaxis for both relativism and transcendance.” Latour (2005, pp. 228-229) elaborates, saying:

“Standards and metrology solve practically the question of relativity that seems to intimidate so many people: Can we obtain some sort of universal agreement? Of course we can! Provided you find a way to hook up your local instrument to one of the many metrological chains whose material network can be fully described, and whose cost can be fully determined. Provided there is also no interruption, no break, no gap, and no uncertainty along any point of the transmission. Indeed, traceability is precisely what the whole of metrology is about! No discontinuity allowed, which is just what ANT [Actor Network Theory] needs for tracing social topography. Ours is the social theory that has taken metrology as the paramount example of what it is to expand locally everywhere, all while bypassing the local as well as the universal. The practical conditions for the expansion of universality have been opened to empirical inquiries. It’s not by accident that so much work has been done by historians of science into the situated and material extension of universals. Given how much modernizers have invested into universality, this is no small feat.
“As soon as you take the example of scientific metrology and standardization as your benchmark to follow the circulation of universals, you can do the same operation for other less traceable, less materialized circulations: most coordination among agents is achieved through the dissemination of quasi-standards.”

As Rasch (1980: xx) understood, “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Though some metrologically informed traceability networks have begun to emerge in education and health care (for instance, Fisher & Stenner, 2013, 2015; Stenner & Fisher, 2013), virtually everything remains to be done to make the coordination across stakeholders as fully elaborated as the standards in the natural sciences.

References

Alder, K. (2002). The measure of all things: The seven-year odyssey and hidden error that transformed the world. New York: The Free Press.

Amato, N., & White, S. (2013, December 7). IIRC releases International Integrated Reporting Framework. Journal of Accountancy. Retrieved from http://www.journalofaccountancy.com/news/2013/dec/20139207.html

Andrich, D. (1988). Sage University Paper Series on Quantitative Applications in the Social Sciences. Vol. series no. 07-068: Rasch models for measurement. Beverly Hills, California: Sage Publications.

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

Andrich, D. (2010). Sufficiency and conditional estimation of person parameters in the polytomous Rasch model. Psychometrika, 75(2), 292-308.

Anielski, M. (2007). The economics of happiness: Building genuine wealth. Gabriola, British Columbia: New Society Publishers.

Ashworth, W. J. (2004, 19 November). Metrology and the state: Science, revenue, and commerce. Science, 306(5700), 1314-1317.

Baxter, W. T. (1979). Accounting standards: Boon or curse? In The Emmanuel Saxe distinguished lectures in accounting. http://newman.baruch.cuny.edu/digital/saxe/saxe_1978/baxter_79.htm.

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

De Boeck, P., & Wilson, M. (Eds.). (2004). Explanatory item response models: A generalized linear and nonlinear approach. Statistics for Social and Behavioral Sciences). New York: Springer-Verlag.

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

Dewey, J. (2012). Unmodern philosophy and modern philosophy (P. Deen, Ed.). Carbondale, Illinois: Southern Illinois University Press.

Editorial. (2010, 10 June). Accounting standards: To FASB or not to FASB? The Economist, http://www.economist.com/node/16319655.

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-155). London: Routledge.

Ekins, P. (1999). Economic growth and environmental sustainability: The prospects for green growth. New York: Routledge.

Ekins, P., Dresner, S., & Dahlstrom, K. (2008, March/April). The four-capital method of sustainable development evaluation. European Environment, 18(2), 63-80.

Ekins, P., Hillman, M., & Hutchison, R. (1992). The Gaia atlas of green economics (Foreword by Robert Heilbroner). New York: Anchor Books.

Ekins, P., & Voituriez, T. (2009). Trade, globalization and sustainability impact assessment: A critical look at methods and outcomes. London, England: Earthscan Publications Ltd.

Engelhard, G., Jr. (2012). Invariant measurement: Using Rasch models in the social, behavioral, and health sciences. New York: Routledge Academic.

Everett, J. D. (1875). Illustrations of the C. G. S. system of units. London, England: Taylor & Francis.

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. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a, November 19). Draft legislation on development and adoption of an intangible assets metric system. Retrieved 6 January 2011, from https://livingcapitalmetrics.wordpress.com/2009/11/19/draft-legislation/

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

Fisher, W. P., Jr. (2009c). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (Tech. Rep. No. http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC:. National Institute for Standards and Technology.

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

Fisher, W. P., Jr. (2010b). 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 (http://ssrn.com/abstract=2340674).

Fisher, W. P., Jr. (2010c). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics: Conference Series, 238(1), http://iopscience.iop.org/1742-6596/238/1/012016/pdf/1742-6596_238_1_012016.pdf.

Fisher, W. P., Jr. (2011a). 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. (2011b). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

Fisher, W. P., Jr. (2012a). 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. (2012b, May/June). 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 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2015). A Rasch perspective on the law of supply and demand. Rasch Measurement Transactions, in press.

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, February). Rehabits: A common language of functional assessment. Archives of Physical Medicine and Rehabilitation, 76(2), 113-122.

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 12 January 2014, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b, 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, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

Fisher, W. P., Jr., & Stenner, A. J. (2013a). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings (pp. 1-11). Berlin, Germany: Springer-Verlag.

Fisher, W. P., Jr., & Stenner, A. J. (2013b). Overcoming the invisibility of metrology: A reading measurement network for education and the social sciences. Journal of Physics: Conference Series, 459(012024), http://iopscience.iop.org/1742-6596/459/1/012024.

Fisher, W. P., Jr., & Stenner, A. J. (2015). The role of metrology in mobilizing and mediating the language and culture of scientific facts. Journal of Physics Conference Series, 588(012043).

Fisher, W. P., Jr., & Stenner, A. J. (2015). Theory-based metrological traceability in education: A reading measurement network. Measurement, in review.

Fisher, W. P., Jr., & Wilson, M. (2015). Building a productive trading zone in educational assessment research and practice. Pensamiento Educativo, in review.

Fisher, W. P., Jr., & Wright, B. D. (1994). Introduction to probabilistic conjoint measurement theory and applications (W. P. Fisher, Jr., & B. D. Wright, Eds.) [Special issue]. International Journal of Educational Research, 21(6), 559-568.

Galison, P. (1997). Image and logic: A material culture of microphysics. Chicago: University of Chicago Press.

Gleeson-White, J. (2015). Six capitals, or can accountants save the planet? Rethinking capitalism for the 21st century. New York: Norton.

Golinski, J. (2012). Is it time to forget science? Reflections on singular science and its history. Osiris, 27(1), 19-36.

Haraway, D. J. (1996). Modest witness: Feminist diffractions in science studies. In P. Galison & D. J. Stump (Eds.), The disunity of science: Boundaries, contexts, and power (pp. 428-441). Stanford, California: Stanford University Press.

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

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

Latour, B. (1990). Postmodern? No, simply amodern: Steps towards an anthropology of science. Studies in History and Philosophy of Science, 21(1), 145-71.

Latour, B. (1993). We have never been modern. Cambridge, Massachusetts: Harvard University Press.

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

Mari, L., & Wilson, M. (2013). A gentle introduction to Rasch measurement models for metrologists. Journal of Physics Conference Series, 459(1), http://iopscience.iop.org/1742-6596/459/1/012002/pdf/1742-6596_459_1_012002.pdf.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-734.

Pendrill, L. (2014, December). Man as a measurement instrument [Special Feature]. NCSLI Measure: The Journal of Measurement Science, 9(4), 22-33.

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, http://iopscience.iop.org/1742-6596/459/1/012057.

Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, p. in press. doi: http://dx.doi.org/10.1016/j.measurement.2015.04.010.

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.

Rogers, J., & White, A. (2015, April 28). Focusing corporate sustainability ratings on what matters. Huffington Post. Retrieved from http://www.huffingtonpost.com/jean-rogers/focusing-corporate-sustai_b_7156148.html.

Stenner, A. J., & Fisher, W. P., Jr. (2013). Metrological traceability in the social sciences: A model from reading measurement. Journal of Physics: Conference Series, 459(012025), http://iopscience.iop.org/1742-6596/459/1/012025.

Stenner, A. J., Fisher, W. P., Jr., Stone, M. H., & Burdick, D. S. (2013, August). Causal Rasch models. Frontiers in Psychology: Quantitative Psychology and Measurement, 4(536), 1-14 [doi: 10.3389/fpsyg.2013.00536].

Williamson, O. E. (1981, November). The economics of organization: The transaction cost approach. The American Journal of Sociology, 87(3), 548-577.

Williamson, O. E. (1991). Economic institutions: Spontaneous and intentional governance [Special issue]. Journal of Law, Economics, & Organization: Papers from the Conference on the New Science of Organization, 7, 159-187.

Williamson, O. E. (2005). The economics of governance. American Economic Review, 95(2), 1-18.

Wilson, M. (Ed.). (2004). National Society for the Study of Education Yearbooks. Vol. 103, Part II: Towards coherence between classroom assessment and accountability. Chicago, Illinois: University of Chicago Press.

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

Wilson, M. R. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46, 3766-3774.

Wilson, M., Mari, L., Maul, A., & Torres Irribarra, D. (2015). A comparison of measurement concepts across physical science and social science domains: Instrument design, calibration, and measurement. Journal of Physics: Conference Series, 588(012034), http://iopscience.iop.org/1742-6596/588/1/012034.

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. (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.

Wright, B. D., & Stone, M. H. (1999). Measurement essentials. Wilmington, DE: Wide Range, Inc. [http://www.rasch.org/measess/me-all.pdf].

Young, J. J., & Williams, P. F. (2010, August). Sorting and comparing: Standard-setting and “ethical” categories. Critical Perspectives on Accounting, 21(6), 509-521.

Another Take on the Emerging Paradigm Shift

November 8, 2014

Over the course of human history, people have usually been able to rely on some stable source of authority and control in their lives, be it religion, the king or queen, or the social order itself. However benevolent or malevolent a regime might be, usually there have been clear lines along which blame or credit can be assigned.

So, even though the complexity and scale of success and failure in today’s world provide ample evidence that no one exerts centralized control over events, it is not surprising that many people today still find it comforting to think some individuals or groups must be manipulating others to their own ends. There is, however, an alternative point of view that may provide a more productive path toward effective action.

After all, efforts to date that have focused on the removal and replacement of any given group that appears to be in control have simply resulted in an alteration of the system, and not the institution of a fundamentally new system. Thus, socialist and communist governments have failed in large part because they were unable to manage resources as effectively as capitalist systems do (which is, of course, not all that well). That is, despite the appearance of having put in place a radically different system of priorities, the constraints of socioeconomics themselves did not change in the context of socialist and communist regimes.

The individual incumbents of social and economic positions have nothing whatsoever to do with the creation of the socioeconomic system’s likelihoods of success and failure, and if they had not accepted their roles in that system, others would have. Changing the system is much more difficult, both conceptually and practically, than merely assigning blame and replacing an individual or group with another individual or group. To the extent the system remains the same, changing the occupants within it makes little difference.

The idea is much the same as was realized in industry when it shifted from quality control’s “tail-chopping” methods to continuous quality improvement’s “curve-shifting” methods. In the former, a certain ratio of acceptable to malformed parts is dictated by the system’s materials and processes. Quality control simply removes the bad parts from the production line and does nothing to change the system. Since quality is often normally distributed, taking the statistical shape of a bell curve, it is accordingly inevitable that cutting off the bad end of that distribution (tail-chopping) only results in it being filled in again in the next production cycle.

Continuous quality improvement methods, in contrast, focus on changing the system and on reducing the likelihood of producing bad parts. Efforts of these kind move the entire quality distribution up the scale so that no parts fall in the previous distribution’s bad tail at all. Of course, the outcomes of our socioeconomic system’s processes are very different from the manufacturing of machine parts. The point of this simple illustration is only that there is remarkable value in thinking less about removing undesired individuals from a process and in thinking more about changing the process itself.

There is no denying that those who seem to be in control benefit disproportionately from others’ efforts. But even though they have had little or nothing to do with creating the system that confers these benefits on them, they certainly do have a vested interest in maintaining that system. This fact reveals another important aspect of any solution that will prove truly viable: the new system must provide benefits not available under the old one. The shift from old to new cannot be a matter of mere will power or organizational efficiency. It must come about as a result of the attractions offered by the new system, which motivate behavior changes universally with little or no persuasion. Qualitatively different classes of opportunities and rewards can come about only by integrating into the system features of the environment that were excluded from the previous system. The central problem of life today is how to provoke this kind of shift and its new integrations.

We can begin to frame this problem in its proper context when we situate it horizontally as an ecological problem and vertically as an evolutionary one. In the same way that ecological niches define the evolutionary opportunities available to species of plants and animals, historical and cultural factors set up varying circumstances to which human societies must adapt. Biological and social adaptations both become increasingly complex over time, systematically exhibiting characteristic patterns in the ways matter, energy, and information are functionally integrated.

The present form of contemporary global society has evolved largely in terms of the Western European principles of modern science, capitalism, and democracy. These principles hinge on the distinction between a concrete, solid, and objective world and an impressionistic, intuitive, and subjective mind. For instance, science and economics focus traditionally on measuring and managing material things and processes, like volts, meters, kilograms, barrels, degrees Celsius, liters, speed, flows, etc. Human, social, and environmental issues are treated statistically, not in terms of standardized metric units, and they are economically regarded as “externalities” excluded from profit and loss calculations.

So, if qualitatively different classes of opportunities and rewards can come about only by integrating into the system features of the environment that were excluded from the previous system, what can we do to integrate the subjective with the objective, and to also then incorporate standardized metric units for the externalities of human, social, and environmental capital into science and economics? The question demands recognition of a) a new system of ecological niches with their own unique configurations of horizontal relationships, and b) the evolution of new species capable of adapting to life in these niches.

The problem is compounded by the complexity of seeing the new system of niches as emerging from the existing system of ecological relationships. Economically speaking, today’s cost centers will be tomorrow’s profit drivers. Scientifically speaking, sources of new repeatable and stable phenomena will have to be identified in what are today assumed to be unrepeatable and unstable phenomena, and will then have to be embodied in instrumental ensembles.

The immediate assumption, which we will have to strive to overcome, is that any such possibilities for new economic and scientific opportunities could hardly be present in the world today and not be widely known and understood. A culturally ingrained presupposition we all share to some extent is that objective facts are immediately accessible and become universally adopted for their advantages as soon as they are recognized. Claims to the contrary can safely be ignored, even if, or perhaps especially if, they represent a truly original potential for system change.

This assumption is an instance of what behavioral economists like Simon and Kahnemann refer to as bounded rationality, which is the idea that language and culture prethink things for us in ways we are usually unaware of. Research has shown that many decisions in daily life are tinged with emotion, such that a certain kind of irrationality takes an irrefutable place in how we think. Examples include choices involving various combinations of favorable and unfavorable odds of profiting from some exchange. Small but sure profits are often ignored in favor of larger and less sure profits, or mistaken calculations are assumed correct, to the disadvantage of the decision maker. There is surely method in the madness, but the pure rationality of an ideal thought process can no longer be accommodated.

Given the phenomenon of bounded rationality, and the complexity of the metasystematic shift that’s needed, how is change to be effected? As Einstein put it, problems of a certain kind cannot be solved from within the same framework that gave rise to them. As long as we continue to think in terms of marshalling resources to apply to the solution of a problem we have failed in conceiving the proper magnitude and scope of the problem we face.

We must instead think in terms of problem-solution units that themselves embody a new evolutionary species functioning within a new system of ecological niches. And these species-niche combinations must be born fully functional and viable, like birds from lizard eggs, caught up in the flow and play of their matter, energy and information streams from the moment of their arrival.

A vitally important aspect of this evolutionary leap is that the new system emerge of its own accord, seemingly with a will of its own. But it will not take shape as a result of individuals or groups deliberately executing a comprehensive design. There will be no grand master architect, though the co-incidence of multiple coordinations and alignments will seem so well planned that many may assume one exists.

It may be, however, that a new spontaneously self-organizing culture might be grown from a few well-placed spores or seeds. The seeds themselves need to be viable in terms of their growth potential and the characteristics of the particular species involved. But equally important are the characteristics of the environment in which the seeds are planted. Bernstein (2004) describes four conditions necessary to the birth of plenty in the modern world:

  1. Property rights: those who might create new forms of value need to own the fruits of their labors.
  2. Scientific rationalism: innovation requires a particular set of conceptual tools and a moral environment in which change agents need not fear retribution.
  3. Capital markets: investors must be able to identify entrepreneurs and provide them with the funds they need to pursue their visions.
  4. Transportation/communications: new products and the information needed to produce and market them must have efficient channels in which to move.

If we take the new emerging culture as unmodern, nonmodern, or amodern, might a new paradigm of plenty similarly take shape as these four conditions are applied not just to manufactured capital, land, and labor, but to human capital (abilities, health, performance), social capital (trust, honesty, dependability, etc.), and natural capital (the environmental services of watersheds, fisheries, estuaries, forests, etc.)? Should not we own legal title to defined shares of each form of capital? Should not science be systematically employed in research on each form of capital? Should not investments in each form of capital be accountable? Should not each form of capital be mobile and fungible within established networks? Should not there be common languages serving as common currencies for the exchange of each form of capital? Instead of assuming the answers to these questions are uniformly “No,” should not we at least entertain them long enough to firmly establish why they cannot be “Yes”?

An Entrepreneurial Investment Model Alternative to Picketty’s Taxation Approach to Eliminating Wealth Disparities

May 14, 2014

Is taxation the only or the best solution to inequality? The way discussions of wealth disparities inevitably focus on variations in how, whom or what to tax, it is easy to assume there are no viable alternatives to taxation. But if the point is to invest in those with the most potential for making significant gains in productivity, so as to maximize the returns we realize, do we not wrongly constrain the domain of possible solutions when we misconceive an entrepreneurial problem in welfare terms?

Why can’t we require minimum levels of investment in social capital stocks and bonds offered by schools, hospitals, NGOs, etc? In human capital instruments offered by individuals? Why should not we expect those investments to be used to create new value? What supposed law of nature says it is impossible to associate new human, social and environmental value with stable and meaningful prices? And if there is such a law (such as Kenneth Arrow (1963) proposed), how can we break it? Why can’t we reconceive human and social capital stocks and flows in new ways?

There is one very good reason why we cannot now make such requirements, and it is the same reason why liberals (including me) had better become accustomed to accepting the failure of their agenda. That reason is this: social and environmental externalities. Inequality is inevitable only as long as we do not change the ways we deal with externalities. They can no longer be measured and managed in the same ways. They must be put on the books, brought into the models, measured scientifically, and traded in efficient markets. We have to invent accountability and accounting systems that harness the energy of the profit motive for the greater good—that actually grow authentic wealth and not mere money—and we have to do this far more effectively than has ever been done before.

It’s a tall order. But there are resources available to us that have not yet been introduced into the larger conversation. There are options to consider that need close study and creative experimentation. Proceeding toward the twin futilities of premature despair or unrealistic taxation will only set up another round of self-fulfilling prophecies inexorably grinding to yet another unforeseen but fully foretold disaster. Conversations about how to shape the roles, rules and institutions that make markets what they are (Miller and O’Leary, 2007) need to take place for human, social, and natural capital (Fisher and Stenner, 2011b). Indeed, those conversations are already well underway, as can be seen in the prior entries in this blog and in the sources listed below.

Arrow, K. J. (1963). Uncertainty and the welfare economics of medical care. American Economic Review, 53, 941-973.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2009a). 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 (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology (11 pages).

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

Fisher, W. P. J. (2010b). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital (http://ssrn.com/abstract=2340674). Bridge to Business Postdoctoral Certification, Freeman School of Business: Tulane University.

Fisher, W. P., Jr. (2010c, June 13-16). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Ed.), https://conference.cbs.dk/index.php/rasch/Rasch2010/paper/view/824. Probabilistic models for measurement in education, psychology, social science and health: Celebrating 50 years since the publication of Rasch’s Probabilistic Models. FUHU Conference Centre, Copenhagen, Denmark: University of Copenhagen School of Business.

Fisher, W. P., Jr. (2011a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

Fisher, W. P., Jr. (2011b, Thursday, September 1). Measurement, metrology and the coordination of sociotechnical networks. In S. Bercea (Ed.), New Education and Training Methods. International Measurement Confederation (IMEKO). Jena, Germany: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf.

Fisher, W. P., Jr. (2012a). 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. (2012b, May/June). 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 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences. http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b, 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: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf.

Fisher, W. P., Jr., & Stenner, A. J. (2013a). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings (pp. 1-11). Berlin, Germany: Springer-Verlag.

Fisher, W. P., Jr., & Stenner, A. J. (2013b). Overcoming the invisibility of metrology: A reading measurement network for education and the social sciences. Journal of Physics: Conference Series, 459(012024), http://iopscience.iop.org/1742-6596/459/1/012024.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-734.

Professional capital as product of human, social, and decisional capitals

April 18, 2014

Leslie Pendrill gave me a tip on a very interesting book, Professional Capital, by Michael Fullan. The author’s distinction between business capital and professional capital is somewhat akin to my distinction (Fisher, 2011) between dead and living capital. The primary point of contact between Fullan’s sense of capital and mine stems from his inclusion of social and decisional capital as crucial enhancements of human capital.

Of course, defining human capital as talent, as Fullan does, is not going to go very far toward supporting generalized management of it. Efficient markets require that capital be represented in transparent and universally available instruments (common currencies or metrics). Transparent, systematic representation makes it possible to act on capital abstractly, in laboratories, courts, and banks, without having to do anything at all with the physical resource itself. (Contrast this with socialism’s focus on controlling the actual concrete resources, and the resulting empty store shelves, unfulfilled five-year plans, pogroms and purges, and overall failure.) Universally accessible transparent representations make capital additive (amounts can be accrued), divisible (it can be divided into shares), and mobile (it can be moved around in networks accepting the currency/metric). (See references below for more information.)

Fullan cites research by Carrie Leanna at the U of Pittsburgh showing that teachers with high social capital increased their students math scores by 5.7% more than teachers with low social capital. The teachers with the highest skill levels (most human capital) and high social capital did the overall best. Low-ability teachers in schools with high social capital did as well as average teachers.

This is great, but the real cream of Fullan’s argument concerns the importance of what he calls decisional capital. I don’t think this will likely work out to be entirely separate from human capital, but his point is well taken: the capacity to consistently engage with students with competence, good judgment, insight, inspiration, creative improvisation, and openness to feedback in a context of shared responsibility is vital. All of this is quite consistent with recent work on collective intelligence (Fischer, Giaccardi, Eden, et al., 2005; Hutchins, 2010; Magnus, 2007; Nersessian, 2006; Woolley, Chabris, Pentland, et al., 2010; Woolley and Fuchs, 2011).

And, of course, you can see this coming: decisional capital is precisely what better measurement provides. Integrated formative and summative assessment informs decision making at the individual level in ways that are otherwise impossible. When those assessments are expressed in uniformly interpretable and applicable units of measurement, collective intelligence and social capital are boosted in the ways documented by Leanna as enhancing teacher performance and boosting student outcomes.

Anyway, just wanted to share that. It fits right in with the trading zone concept I presented at IOMW (the slides are available on my LinkedIn page).

Fischer, G., Giaccardi, E., Eden, H., Sugimoto, M., & Ye, Y. (2005). Beyond binary choices: Integrating individual and social creativity. International Journal of Human-Computer Studies, 63, 482-512.

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), 936-938 [http://www.rasch.org/rmt/rmt173.pdf].

Fisher, W. P., Jr. (2004a, Thursday, January 22). Bringing capital to life via measurement: A contribution to the new economics. In R. Smith (Chair), Session 3.3B. Rasch Models in Economics and Marketing. Second International Conference on Measurement. Perth, Western Australia:  Murdoch University.

Fisher, W. P., Jr. (2004b, Friday, July 2). Relational networks and trust in the measurement of social capital. Twelfth International Objective Measurement Workshops. Cairns, Queensland, Australia: James Cook University.

Fisher, W. P., Jr. (2005a). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-179.

Fisher, W. P., Jr. (2005b, August 1-3). Data standards for living human, social, and natural capital. In Session G: Concluding Discussion, Future Plans, Policy, etc. Conference on Entrepreneurship and Human Rights. Pope Auditorium, Lowenstein Bldg, Fordham University.

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-1093 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2008a, 3-5 September). New metrological horizons: Invariant reference standards for instruments measuring human, social, and natural capital. 12th IMEKO TC1-TC7 Joint Symposium on Man, Science, and Measurement. Annecy, France: University of Savoie.

Fisher, W. P., Jr. (2008b, March 28). Rasch, Frisch, two Fishers and the prehistory of the Separability Theorem. In J. William P. Fisher (Ed.), Session 67.056. Reading Rasch Closely: The History and Future of Measurement. American Educational Research Association. New York City [Paper available at SSRN: http://ssrn.com/abstract=1698919%5D: Rasch Measurement SIG.

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 (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology (11 pages).

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

Fisher, W. P. J. (2010b). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital (p. http://ssrn.com/abstract=2340674). Bridge to Business Postdoctoral Certification, Freeman School of Business: Tulane University.

Fisher, W. P., Jr. (2010c). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics: Conference Series, 238(1), http://iopscience.iop.org/1742-6596/238/1/012016/pdf/1742-6596_238_1_012016.pdf.

Fisher, W. P., Jr. (2011a). 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. (2011b). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com [Online]. Available: http://ssrn.com/abstract=1739386 (Accessed 18 January 2011).

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., & Stenner, A. J. (2005, Tuesday, April 12). Creating a common market for the liberation of literacy capital. In R. E. Schumacker (Ed.), Rasch Measurement: Philosophical, Biological and Attitudinal Impacts. American Educational Research Association. Montreal, Canada: Rasch Measurement SIG.

Fisher, W. P., Jr., & Stenner, A. J. (2011a, January). Metrology for the social, behavioral, and economic sciences. Available: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36 (Accessed 12 January 2014).

Fisher, W. P., Jr., & Stenner, A. J. (2011b, 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: http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf.

Hutchins, E. (2010). Cognitive ecology. Topics in Cognitive Science, 2, 705-715.

Magnus, P. D. (2007). Distributed cognition and the task of science. Social Studies of Science, 37(2), 297-310.

Nersessian, N. J. (2006, December). Model-based reasoning in distributed cognitive systems. Philosophy of Science, pp. 699-709.

Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010, 29 October). Evidence for a collective intelligence factor in the performance of human groups. Science, pp. 686-688.

Woolley, A. W., & Fuchs, E. (2011, September-October). Collective intelligence in the organization of science. Organization Science, pp. 1359-1367.

Six Classes of Results Supporting the Measurability of Human Functioning and Capability

April 12, 2014

Another example of high-level analysis that suffers from a lack of input from state of the art measurement arises in Nussbaum (1997, p. 1205), where the author remarks that it is now a matter of course, in development economics, “to recognize distinct domains of human functioning and capability that are not commensurable along a single metric, and with regard to which choice and liberty of agency play a fundamental structuring role.” Though Nussbaum (2011, pp. 58-62) has lately given a more nuanced account of the challenges of measurement relative to human capabilities, appreciation of the power and flexibility of contemporary measurement models, methods, and instruments remains lacking. For a detailed example of the complexities and challenges that must be addressed in the context of global human development, which is Nussbaum’s area of interest, see Fisher (2011).

Though there are indeed domains of human functioning and capability that are not commensurable along a single metric, they are not the ones referred to by Nussbaum or the texts she cites. On the contrary, six different approaches to establishing the measurability of human functioning and capability have been explored and proven as providing, especially in their composite aggregate, a substantial basis for theory and practice (modified from Fisher, 2009, pp. 1279-1281). These six classes of results speak to the abstract, mathematical side of the paradox noted by Ricoeur (see previous post here) concerning the need to simultaneously accept roles for abstract ideal global universals and concrete local historical contexts in strategic planning and thinking. The six classes of results are:

  1. Mathematical proofs of the necessity and sufficiency of test and survey scores for invariant measurement in the context of Rasch’s probabilistic models (Andersen, 1977, 1999; Fischer, 1981; Newby, Conner, Grant, and Bunderson, 2009; van der Linden, 1992).
  2. Reproduction of physical units of measurement (centimeters, grams, etc.) from ordinal observations (Choi, 1997; Moulton, 1993; Pelton and Bunderson, 2003; Stephanou and Fisher, 2013).
  3. The common mathematical form of the laws of nature and Rasch models (Rasch, 1960, pp. 110-115; Fisher, 2010; Fisher and Stenner, 2013).
  4. Multiple independent studies of the same constructs on different (and common) samples using different (and the same) instruments intended to measure the same thing converge on common units, defining the same objects, substantiating theory, and supporting the viability of standardized metrics (Fisher, 1997a, 1997b, 1999, etc.).
  5. Thousands of peer-reviewed publications in hundreds of scientific journals provide a wide-ranging and diverse array of supporting evidence and theory.
  6. Analogous causal attributions and theoretical explanatory power can be created in both natural and social science contexts (Stenner, Fisher, Stone, and Burdick, 2013).

What we have here, in sum, is a combination of Greek axiomatic and Babylonian empirical algorithms, in accord with Toulmin’s (1961, pp. 28-33) sense of the contrasting principled bases for scientific advancement. Feynman (1965, p. 46) called for less of a focus on the Greek chain of reasoning approach, as it is only as strong as its weakest link, whereas the Babylonian algorithms are akin to a platform with enough supporting legs that one or more might fail without compromising its overall stability. The variations in theory and evidence under these six headings provide ample support for the conceptual and practical viability of metrological systems of measurement in education, health care, human resource management, sociology, natural resource management, social services, and many other fields. The philosophical critique of any type of economics will inevitably be wide of the mark if uninformed about these accomplishments in the theory and practice of measurement.

References

Andersen, E. B. (1977). Sufficient statistics and latent trait models. Psychometrika, 42(1), 69-81.

Andersen, E. B. (1999). Sufficient statistics in educational measurement. In G. N. Masters & J. P. Keeves (Eds.), Advances in measurement in educational research and assessment (pp. 122-125). New York: Pergamon.

Choi, S. E. (1997). Rasch invents “ounces.” Rasch Measurement Transactions, 11(2), 557 [http://www.rasch.org/rmt/rmt112.htm#Ounces].

Feynman, R. (1965). The character of physical law. Cambridge, Massachusetts: MIT Press.

Fischer, G. H. (1981). On the existence and uniqueness of maximum-likelihood estimates in the Rasch model. Psychometrika, 46(1), 59-77.

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. (1997). What scale-free measurement means to health outcomes research. Physical Medicine & Rehabilitation State of the Art Reviews, 11(2), 357-373.

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

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), http://iopscience.iop.org/1742-6596/238/1/012016/pdf/1742-6596_238_1_012016.pdf.

Fisher, W. P., Jr. (2011). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

Fisher, W. P., Jr., & Stenner, A. J. (2013). On the potential for improved measurement in the human and social sciences. In Q. Zhang & H. Yang (Eds.), Pacific Rim Objective Measurement Symposium 2012 Conference Proceedings (pp. 1-11). Berlin, Germany: Springer-Verlag.

Moulton, M. (1993). Probabilistic mapping. Rasch Measurement Transactions, 7(1), 268 [http://www.rasch.org/rmt/rmt71b.htm].

Newby, V. A., Conner, G. R., Grant, C. P., & Bunderson, C. V. (2009). The Rasch model and additive conjoint measurement. Journal of Applied Measurement, 107(4), 348-354.

Nussbaum, M. (1997). Flawed foundations: The philosophical critique of (a particular type of) economics. University of Chicago Law Review, 64, 1197-1214.

Nussbaum, M. (2011). Creating capabilities: The human development approach. Cambridge, MA: The Belknap Press.

Pelton, T., & Bunderson, V. (2003). The recovery of the density scale using a stochastic quasi-realization of additive conjoint measurement. Journal of Applied Measurement, 4(3), 269-281.

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.

Rasch, G. (1977). On specific objectivity: An attempt at formalizing the request for generality and validity of scientific statements. Danish Yearbook of Philosophy, 14, 58-94.

Stenner, A. J., Fisher, W. P., Jr., Stone, M. H., & Burdick, D. S. (2013). Causal Rasch models. Frontiers in Psychology: Quantitative Psychology and Measurement, 4(536), 1-14.

Stephanou, A., & Fisher, W. P., Jr. (2013). From concrete to abstract in the measurement of length. Journal of Physics Conference Series, 459, http://iopscience.iop.org/1742-6596/459/1/012026.

Toulmin, S. E. (1961). Foresight and understanding: An enquiry into the aims of science. London, England: Hutchinson.

van der Linden, W. J. (1992). Sufficient and necessary statistics. Rasch Measurement Transactions, 6(3), 231 [http://www.rasch.org/rmt/rmt63d.htm].

 

On the Criterion Institute’s Leaders Shaping Markets initiative

November 14, 2013

The Criterion Institute’s Leaders Shaping Markets initiative is an encouraging development in large part because of its focus on systems level change. As the Institute recognizes, the questions being raised and the resources being invested are essential to overcoming recurrent problems of fragmentation and marginalization in efforts being made in more piecemeal fashion across a number of other arenas.

Of particular interest from the Institute’s second roundtable session is Joy Anderson’s list of Strategies for Shaping Market Systems. Anderson presents five strategies:

  1. reframing the issues, problems, and boundaries of the system;
  2. engaging systems of power, elegantly;
  3. continuously identifying leverage points in the system;
  4. building structures and leadership for sustained systems-level disruption; and
  5. attending to change over time and across context.

Reframing is the right place to start. As I’ve said elsewhere in this blog, the problem is the problem. At this level of complexity, problems cannot be solved from within the same paradigm they were born from. Conceiving ways of redefining problems that truly reframe the issues and boundaries of a system is hard enough, but implementing them is even harder.

From my point of view, philosophically, the central problem that makes everything so difficult has to do with our deeply ingrained Western habits of thought around not viewing problems and solutions as of a piece, as wholes in which each implies the other. As long as we keep defining problems and solutions in ways that separate them, as though the solution is in no way involved in perpetuating the problem, we are hopelessly stuck.

So we restrict our options for solving problems by the way we frame the issues. And when we misidentify the problem, as when we fail to properly frame it, then we will likely not only not solve it, we will make it worse. That seems to be exactly what’s been going on in the struggle for economic and social justice for decades and centuries.

So if we reframe the problem of shaping markets around the mutual implication of problems and solutions, how do we move to the next step, to engaging systems of power, elegantly? There are a lot of deep and complex philosophical concepts involved here, but we can cut to the chase and note that our language and tools embody problem-solution unities. Social ecologies of relationships define the meanings and uses of things and ideas.

One way of engaging systems of power elegantly to shape markets might then be to harness the power driving those markets in new, more efficient and meaningful ways. The question that then immediately arises concerns the next of Anderson’s five points: where do we find the leverage in the system that would enable the harnessing of its power?

There is likely no greater concentration of power in markets than the profit motive. How might it become the primary lever for engaging the power of the market? We might, for instance, deploy tools and ideas that co-opt the interests of the systems of power by enhancing the predictability of market forces and sustainability of profits. Concentrating now on dwelling within the problem-solution unity of how to shape markets, we can tap into a key factor that makes markets efficient: we manage what we measure, and management is facilitated when we can measure quality and quantity cheaply and easily.

Common currencies for the exchange of value are essential not just to trade and commerce, but also take shape as the standard metrics employed in science, engineering, music, and as the signs and symbols of basic communication. Money is such an easy to manage measure of value that the problems we are addressing here stem in large part from using it too exclusively as a proxy for the authentic wealth we really want. Engaging with systems of power elegantly also then requires us to think in terms of extending the power of standard units of measurement into the new domains of intangible assets: human, social, and natural capital.

This is where we arrive at the structures for sustained system-level disruption. Current economic models and financial spreadsheets focus on the three classic forms of capital: land, labor, and manufactured tools/commodities. (Money, as liquid capital, is fungible relative to all three.) Of these three, we have a metric system for measuring and managing only property and manufactured tools/commodities.

Green economics offers an alternative four-capitals model that adds social capital and reframes land as natural capital and labor as human capital. Both of the latter are found to be far more complex and valuable than their usual reductions to a piece of ground or “hands” would suggest. Human capital involves health, abilities, and motivations; natural capital includes the earth’s air and water purification systems, and food supplies. The addition of social capital is justified on the grounds that, without it, markets are impossible.

What we do not have is a metric system for three of the four forms of capital. Nor do we have the legal and financial systems needed to bring these forms of capital to life in efficient markets, to make them recognized and accepted in banks and courts of law. We further also do not have leaders aware of the need for these structures, and of the established basis in scientific research that makes them viable.

The science is complex and technical, but it brings to bear practical capacities for meaningful, individual level, qualitatively informative and quantitatively rigorous measurement. There is considerable elegance in this method of approaching engagement with the systems of power. There is mathematical beauty in the symmetry and harmony of instruments tuned to the same scales. There is exquisite grace in the way the program for shaping markets grows organically from the seeds of existing markets. The human value of enabling the realization of heretofore unreachable degrees of individual potentials would be enormous, as would be the social value of being able to make returns on investments in education, health care, social services, and the environment accountable.

Successful new markets harnessing the profit motive in the name of socially responsible and sustainable economies well ought to provoke a new cultural renaissance as the proven relationships between higher rates of educational attainment and health, community relations, and environmental quality are born out. The challenges are huge, but properly framing the problems and their solutions will unify our energies in common purpose like never before, bringing joy to the effort.

For further reading along these lines, see:

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, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

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, http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf

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). Washington, DC: National Science Foundation, http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36

Fisher, W. P., Jr. (2012, May/June). 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, http://ses-standards.org/associations/3698/files/2011WSDthirdplacepaper.pdf or http://ssrn.com/abstract=2083975

Fisher, W. P., Jr. (2009, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement, 42(9), 1278-1287, http://doi:10.1016/j.measurement.2009.03.014

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66, http://ssrn.com/abstract=1698867

Fisher, W. P. J. (2010). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital. Qualifying Paper, Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University, http://ssrn.com/abstract=2340674

https://livingcapitalmetrics.wordpress.com/2010/01/13/reinventing-capitalism/

Dispelling Myths about Measurement in Psychology and the Social Sciences

August 27, 2013

Seven common assumptions about measurement and method in psychology and the social sciences stand as inconsistent anomalies in the experience of those who have taken the trouble to challenge them. As evidence, theory, and instrumentation accumulate, will we see a revolutionary break and disruptive change across multiple social and economic levels and areas as a result? Will there be a slower, more gradual transition to a new paradigm? Or will the status quo simply roll on, oblivious to the potential for new questions and new directions? We shall see.

1. Myth: Qualitative data and methods cannot really be integrated with quantitative data and methods because of opposing philosophical assumptions.

Fact: Qualitative methods incorporate a critique of quantitative methods that leads to a more scientific theory and practice of measurement.

2. Myth: Statistics is the logic of measurement.

Fact: Statistics did not emerge as a discipline until the 19th century, while measurement, of course, has been around for millennia. Measurement is modeled at the individual level within a single variable whereas statistics model at the population level between variables. Data are fit to prescriptive measurement models using the Garbage-In, Garbage-Out (GIGO) Principle, while descriptive statistical models are fit to data.

3. Myth: Linear measurement from ordinal test and survey data is impossible.

Fact: Ordinal data have been used as a basis for invariant linear measures for decades.

4. Myth: Scientific laws like Newton’s laws of motion cannot be successfully formulated, tested, or validated in psychology and the social sciences.

Fact: Mathematical laws of human behavior and cognition in the same form as Newton’s laws are formulated, tested, and validated in numerous Rasch model applications.

5. Myth: Experimental manipulations of psychological and social phenomena are inherently impossible or unethical.

Fact: Decades of research across multiple fields have successfully shown how theory-informed interventions on items/indicators/questions can result in predictable, consistent, and substantively meaningful quantitative changes.

6. Myth: “Real” measurement is impossible in psychology and the social sciences.

Fact: Success in predictive theory, instrument calibration, and in maintaining stable units of comparison over time are all evidence supporting the viability of meaningful uniform units of measurement in psychology and the social sciences.

7. Myth: Efficient economic markets can incorporate only manufactured and liquid capital, and property. Human, social, and natural capital, being intangible, have permanent status as market externalities as they cannot be measured well enough to enable accountability, pricing, or transferable representations (common currency instruments).

Fact: The theory and methods necessary for establishing an Intangible Assets Metric System are in hand. What’s missing is the awareness of the scientific, human, social, and economic value that would be returned from the admittedly very large investments that would be required.

References and examples are available in other posts in this blog, in my publications, or on request.