Archive for the ‘transparent representation’ 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.

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.

What the Economy Needs?

September 5, 2012

Expanding on remarks made by Thomas Friedman in the course of an interview with Charlie Rose broadcast on August 31, 2012…

Friedman broke the problem down to three key points. We have to have 1) a plan, 2) a fair tax contribution from the rich, and 3) aspirations for improving the overall quality of life, economically and  democratically.

The plan outlined from various points of view in this blog is to create a scientific and market infrastructure for intangible assets (human, social and natural capital), assets amounting to at least 90%of the capital under management.

The plan is fair in its advancement of equal opportunity to invest in and realize returns from one’s skills, motivations, health and trustworthiness. Everyone will be able to invest in, and receive their share of the profits from, the human, social, and natural capital stocks of individuals, communities, schools, hospitals, social service agencies, firms, etc. The rich will then both contribute to the advancement of the greater good at the same time they are able to profit from the growth in the authentic wealth created by improvements to human, community, and environmental value.

The plan aspires to great accomplishments in the depth and breadth of the innovation it will facilitate, its fulfillment of democratic principles, and the new economic growth it promises.

And so I would now like to raise a couple of sets of questions. What if all the money put into Medicare, Medicaid, education, HUD, food stamps, the EPA, etc. was instead invested in an infrastructure for intangible assets metrology and HSN capital stocks (individual, organizational–school, hospital, nonprofit, NGO, firm–and community)? Usually, talk of letting the market solve social and environmental problems is nothing but a self-serving excuse for allowing greed to rule at the expense of the greater good. Those so-called market solutions do nothing to actually shape the institutions, rules, and roles by which markets are created, and so the end result would be catastrophic. But there is an essential and unnoticed inconsistency in previously proposed approaches that involves the double standards used in defining and actualizing the various forms of capital.

As previous posts (like this one or this one) in this blog, and several of my publications, have argued, manufactured capital and property have long since been brought to life by transferable representations (titles, deeds, precision quantity measures, etc.) and the various legal, financial, educational, and scientific institutions built up around them. Human, social, and natural capital have not been brought to life and so we remain unable to take proper possession of our own properties, the ones that we most value and on which life, liberty, and happiness are most dependent.

But what if we created the needed market institutions, rules, and roles? What if everyone knew how many shares of community capital they owned, and what the current price of those shares in the market was? What if tuition for an advanced degree was denominated in the shares of literacy capital one obtained, as evident in the increased literacy measures achieved? What if taxes were abolished and minimum investments in human, social, and natural capital stocks were required? What if real, efficient, functional markets in intangible assets were created, and the associated governmental programs and departments were abolished? How much would the federal budget decrease? How much would government shrink? How much might the economy grow if that much money was invested in human, social, and natural capital stocks paying even a minimal reasonable profit?

Another round of questions asks whether we have the optimal social safety net in the current institutional context, or if perhaps that safety net could be significantly improved by following through on the concepts of impact investing and outcome-based budgeting to create a truly sustainable and socially responsible economic system? What if everyone held known numbers of tradable shares of their intangible assets (their skills, motivation, health, trust)? What if the value of those shares was common public knowledge? What if the investment paths to increasing the number and value of shares held were all well known? What if monetary profit could be derived–and could only be derived–by increasing the value of human, social, and natural capital shares? What if groups of people joined together in various kinds of organizations (schools, hospitals, businesses) to collectively grow the value of their authentic wealth? What if lean thinking was applied to the 90% of the capital under management (the human, social, and natural capital) that is currently nearly unmanageable because it is not measured in universally uniform scientific units?

The balance scale is a common symbol of justice. We do not usually aspire to take that symbol as seriously as we could. We ought to have a plan for economic justice that does not have to coerce anyone to acknowledge, pay back, and re-invest in the broad support they received en route to becoming successful. And we ought to have a plan that reinvigorates the aspirations for equal opportunity and freedom that have become a model for people all over the world. Friedman got the broad strokes right. Now’s the time to start filling in the details.

Comments on the New ANSI Human Capital Investor Metrics Standard

April 16, 2012

The full text of the proposed standard is available here.

It’s good to see a document emerge in this area, especially one with such a broad base of support from a diverse range of stakeholders. As is stated in the standard, the metrics defined in it are a good place to start and in many instances will likely improve the quality and quantity of the information made available to investors.

There are several issues to keep in mind as the value of standards for human capital metrics becomes more widely appreciated. First, in the context of a comprehensively defined investment framework, human capital is just one of the four major forms of capital, the other three being social, natural, and manufactured (Ekins, 1992; Ekins, Dresden, and Dahlstrom, 2008). To ensure as far as possible the long term stability and sustainability of their profits, and of the economic system as a whole, investors will certainly want to expand the range of the available standards to include social and natural capital along with human capital.

Second, though we manage what we measure, investment management is seriously compromised by having high quality scientific measurement standards only for manufactured capital (length, weight, volume, temperature, energy, time, kilowatts, etc.). Over 80 years of research on ability tests, surveys, rating scales, and assessments has reached a place from which it is prepared to revolutionize the management of intangible forms of capital (Fisher, 2007, 2009a, 2009b, 2010, 2011a, 2011b; Fisher & Stenner, 2011a, 2011b; Wilson, 2011; Wright, 1999). The very large reductions in transaction costs effected by standardized metrics in the economy at large (Barzel, 1982; Benham and Benham, 2000) are likely to have a similarly profound effect on the economics of human, social, and natural capital (Fisher, 2011a, 2012a, 2012b).

The potential for dramatic change in the conceptualization of metrics is most evident in the proposed standard in the sections on leadership quality and employee engagement. For instance, in the section on leadership quality, it is stated that “Investors will be able to directly compare all organizations that are using the same vendor’s methodology.” This kind of dependency should not be allowed to stand as a significant factor in a measurement standard. Properly constructed and validated scientific measures, such as those that have been in wide use in education, psychology and health care for several decades (Andrich, 2010; Bezruzcko, 2005; Bond and Fox, 2007; Fisher and Wright, 1994; Rasch, 1960; Salzberger, 2009; Wright, 1999), are equated to a common unit. Comparability should never depend on which vendor is used. Rather, any instrument that actually measures the construct of interest (leadership quality or employee engagement) should do so in a common unit and within an acceptable range of error. “Normalizing” measures for comparability, as is suggested in the standard, means employing psychometric methods that are 50 years out of date and that are far less rigorous and practical than need be. Transparency in measurement means looking through the instrument to the thing itself. If particular instruments color or reshape what is measured, or merely change the meaning of the numbers reported, then the integrity of the standard as a standard should be re-examined.

Third, for investments in human capital to be effectively managed, each distinct aspect of it (motivations, skills and abilities, health) needs to be measured separately, just as height, weight, and temperature are. New technologies have already transformed measurement practices in ways that make the necessary processes precise and inexpensive. Of special interest are adaptively administered precalibrated instruments supporting mass customized—but globally comparable—measures (for instance, see the examples at http://blog.lexile.com/tag/oasis/ and that were presented at the recent Pearson Global Research Conference in Fremantle, Australia http://www.pearson.com.au/marketing/corporate/pearson_global/default.html; also see Wright and Bell 1984, Lunz, Bergstrom, and Gershon, 1994, Bejar, et al., 2003).

Fourth, the ownership of human capital needs clarification and legal status. If we consider each individual to own their abilities, health, and motivations, and to be solely responsible for decisions made concerning the disposition of those properties, then, in accord with their proven measured amounts of each type of human capital, everyone ought to have legal title to a specific number of shares or credits of each type. This may transform employment away from wage-based job classification compensation to an individualized investment-based continuous quality improvement platform. The same kind of legal titling system will, of course, need to be worked out for social and natural capital, as well.

Fifth, given scientific standards for each major form of capital, practical measurement technologies, and legal title to our shares of capital, we will need expanded financial accounting standards and tools for managing our individual and collective investments. Ongoing research and debates concerning these standards and tools (Siegel and Borgia, 2006; Young and Williams, 2010) have yet to connect with the larger scientific, economic, and legal issues raised here, but developments in this direction should be emerging in due course.

Sixth, a number of lingering moral, ethical and political questions are cast in a new light in this context. The significance of individual behaviors and decisions is informed and largely determined by the context of the culture and institutions in which those behaviors and decisions are executed. Many of the morally despicable but not illegal investment decisions leading to the recent economic downturn put individuals in the position of either setting themselves apart and threatening their careers or doing what was best for their portfolios within the limits of the law. Current efforts intended to devise new regulatory constraints are misguided in focusing on ever more microscopically defined particulars. What is needed is instead a system in which profits are contingent on the growth of human, social, and natural capital. In that framework, legal but ultimately unfair practices would drive down social capital stock values, counterbalancing ill-gotten gains and making them unprofitable.

Seventh, the International Vocabulary of Measurement, now in its third edition (VIM3), is a standard recognized by all eight international standards accrediting bodies (BIPM, etc.). The VIM3 (http://www.bipm.org/en/publications/guides/vim.html) and forthcoming VIM4 are intended to provide a uniform set of concepts and terms for all fields that employ measures across the natural and social sciences. A new dialogue on these issues has commenced in the context of the International Measurement Confederation (IMEKO), whose member organizations are the weights and standards measurement institutes from countries around the world (Conference note, 2011). The 2012 President of the Psychometric Society, Mark Wilson, gave an invited address at the September 2011 IMEKO meeting (Wilson, 2011), and a member of the VIM3 editorial board, Luca Mari, is invited to speak at the July, 2012 International Meeting of the Psychometric Society. I encourage all interested parties to become involved in efforts of these kinds in their own fields.

References

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

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Bejar, I., Lawless, R. R., Morley, M. E., Wagner, M. E., Bennett, R. E., & Revuelta, J. (2003, November). A feasibility study of on-the-fly item generation in adaptive testing. The Journal of Technology, Learning, and Assessment, 2(3), 1-29; http://ejournals.bc.edu/ojs/index.php/jtla/article/view/1663.

Benham, A., & Benham, L. (2000). Measuring the costs of exchange. In C. Ménard (Ed.), Institutions, contracts and organizations: Perspectives from new institutional economics (pp. 367-375). Cheltenham, UK: Edward Elgar.

Bezruczko, N. (Ed.). (2005). Rasch measurement in health sciences. Maple Grove, MN: JAM Press.

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

Conference note. (2011). IMEKO Symposium: August 31- September 2, 2011, Jena, Germany. Rasch Measurement Transactions, 25(1), 1318.

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

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [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.

Fisher, W. P.. Jr. (2010). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Chair), 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.., University of Copenhagen School of Business, FUHU Conference Centre, Copenhagen, Denmark.

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

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

Fisher, W. P., Jr. (2012b). What the world needs now: A bold plan for new standards. Standards Engineering, 64, in press.

Fisher, W. P., Jr., & Stenner, A. J. (2011a). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, 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). 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., & Wright, B. D. (Eds.). (1994). Applications of probabilistic conjoint measurement. International Journal of Educational Research, 21(6), 557-664.

Lunz, M. E., Bergstrom, B. A., & Gershon, R. C. (1994). Computer adaptive testing. International Journal of Educational Research, 21(6), 623-634.

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.

Salzberger, T. (2009). Measurement in marketing research: An alternative framework. Northampton, MA: Edward Elgar.

Siegel, P., & Borgia, C. (2006). The measurement and recognition of intangible assets. Journal of Business and Public Affairs, 1(1).

Wilson, M. (2011). The role of mathematical models in measurement: A perspective from psychometrics. In L. Mari (Chair), Plenary lecture. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24178/ilm1-2011imeko-005.pdf, Jena, Germany.

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., & Bell, S. R. (1984, Winter). Item banks: What, why, how. Journal of Educational Measurement, 21(4), 331-345 [http://www.rasch.org/memo43.htm].

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

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Reimagining Capitalism Again, Part II: Scientific Credibility in Improving Information Quality

September 10, 2011

The previous posting here concluded with two questions provoked by a close consideration of a key passage in William Greider’s 2003 book, The Soul of Capitalism. First, how do we create the high quality, solid information markets need to punish and reward relative to ethical and sustainable human, social, and environmental values? Second, what can we learn from the way we created that kind of information for property and manufactured capital? There are good answers to these questions, answers that point in productive directions in need of wide exploration and analysis.

The short answer to both questions is that better, more scientifically rigorous measurement at the local level needs to be implemented in a context of traceability to universally uniform standards. To think global and act local simultaneously, we need an efficient and transparent way of seeing where we stand in the world relative to everyone else. Having measures expressed in comparable and meaningful units is an important part of how we think global while acting local.

So, for markets to punish and reward businesses in ways able to build human, social, and environmental value, we need to be able to price that value, to track returns on investments in it, and to own shares of it. To do that, we need a new intangible assets metric system that functions in a manner analogous to the existing metric system and other weights and measures standards. In the same way these standards guarantee high quality information on volume, weight, thermal units, and volts in grocery stores and construction sites, we need a new set of standards for human abilities, performances, and health; for social trust, commitment, and loyalty; and for the environment’s air and water processing services, fisheries, gene pools, etc.

Each industry needs an instrumentarium of tools and metrics that mediate relationships universally within its entire sphere of production and/or service. The obvious and immediate reaction to this proposal will likely be that this is impossible, that it would have been done by now if it was possible, and that anyone who proposes something like this is simply unrealistic, perhaps dangerously so. So, here we have another reason to add to those given in the June 8, 2011 issue of The Nation (http://www.thenation.com/article/161267/reimagining-capitalism-bold-ideas-new-economy) as to why bold ideas for a new economy cannot gain any traction in today’s political discourse.

So what basis in scientific authority might be found for this audacious goal of an intangible assets metric system? This blog’s postings offer multiple varieties of evidence and argument in this regard, so I’ll stick to more recent developments, namely, last week’s meeting of the International Measurement Confederation (IMEKO) in Jena, Germany. Membership in IMEKO is dominated by physicists, engineers, chemists, and clinical laboratorians who work in private industry, academia, and government weights and measures standards institutes.

Several IMEKO members past and present are involved with one or more of the seven or eight major international standards organizations responsible for maintaining and improving the metric system (the Systeme Internationale des Unites). Two initiatives undertaken by IMEKO and these standards organizations take up the matter at issue here concerning the audacious goal of standard units for human, social, and natural capital.

First, the recently released third edition of the International Vocabulary of Measurement (VIM, 2008) expands the range of the concepts and terms included to encompass measurement in the human and social sciences. This first effort was not well informed as to the nature of widely realized state of the art developments in measurement in education, health care, and the social sciences. What is important is that an invitation to further dialogue has been extended from the natural to the social sciences.

That invitation was unintentionally accepted and a second initiative advanced just as the new edition of the VIM was being released, in 2008. Members of three IMEKO technical committees (TC 1-7-13; those on Measurement Science, Metrology Education, and Health Care) cultivate a special interest in ideas on the human and social value of measurement. At their 2008 meeting in Annecy, France, I presented a paper (later published in revised form as Fisher, 2009) illustrating how, over the previous 50 years and more, the theory and practice of measurement in the social sciences had developed in ways capable of supporting convenient and useful universally uniform units for human, social, and natural capital.

The same argument was then advanced by my fellow University of Chicago alum, Nikolaus Bezruczko, at the 2009 IMEKO World Congress in Lisbon. Bezruczko and I both spoke at the 2010 TC 1-7-13 meeting in London, and last week our papers were joined by presentations from six of our colleagues at the 2011 IMEKO TC 1-7-13 meeting in Jena, Germany. Another fellow U Chicagoan, Mark Wilson, a long time professor in the Graduate School of Education at the University of California, Berkeley, gave an invited address contrasting four basic approaches to measurement in psychometrics, and emphasizing the value of methods that integrate substantive meaning with mathematical rigor.

Examples from education, health care, and business were then elucidated at this year’s meeting in Jena by myself, Bezruczko, Stefan Cano (University of Plymouth, England), Carl Granger (SUNY, Buffalo; paper presented by Bezruczko, a co-author), Thomas Salzberger (University of Vienna, Austria), Jack Stenner (MetaMetrics, Inc., Durham, NC, USA), and Gordon Cooper (University of Western Australia, Crawley, WA, Australia; paper presented by Fisher, a co-author).

The contrast between these presentations and those made by the existing IMEKO membership hinges on two primary differences in focus. The physicists and engineers take it for granted that all instrument calibration involves traceability to metrological reference standards. Dealing as they are with existing standards and physical or chemical materials that usually possess deterministically structured properties, issues of how to construct linear measures from ordinal observations never come up.

Conversely, the social scientists and psychometricians take it for granted that all instrument calibration involves evaluations of the capacity of ordinal observations to support the construction of linear measures. Dealing as they are with data from tests, surveys, and rating scale assessments, issues of how to relate a given instrument’s unit to a reference standard never come up.

Thus there is significant potential for mutually instructive dialogue between natural and social scientists in this context. Many areas of investigation in the natural sciences have benefited from the introduction of probabilistic concepts in recent decades, but there are perhaps important unexplored opportunities for the application of probabilistic measurement, as opposed to statistical, models. By taking advantage of probabilistic models’ special features, measurement in education and health care has begun to realize the benefit of broad generalizations of comparable units across grades, schools, tests, and curricula.

Though the focus of my interest here is in the capacity of better measurement to improve the efficiency of human, social, and natural capital markets, it may turn out that as many or more benefits will accrue in the natural sciences’ side of the conversation as in the social sciences’ side. The important thing for the time being is that the dialogue is started. New and irreversible mutual understandings between natural and social scientists have already been put on the record. It may happen that the introduction of a new supply of improved human, social, and natural capital metrics will help articulate the largely, as yet, unstated but nonetheless urgent demand for them.

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.

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

September 10, 2011

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

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

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

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

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

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

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

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

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

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

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

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The Path to a New Consensus: A Practical Procedure for Resolving the Opposition Between Absolute and Relative Standards

August 26, 2011

The possibility of a new nonpartisan consensus on social and economic issues has been raised from time to time lately. I’ve had some ideas fermenting in this area for a while, and it seems like they might be ready for recording here. What I want to take up concerns one of the more contentious aspects of the cultural and political disputes of recent decades. There are important differences between those who want to impose one or another kind of moral or religious standard on society as a whole and those who contend that, within certain limits, such standards are arbitrary and must be determined by each individual or group according to its own values and sense of what makes a community.The oppositions here might seem to be irreconcilable, but is that actually true?

Resolving deep-seated disagreements on this scale requires that all parties accept some baseline rules of engagement. And herein lies the rub, eh? For even something as seemingly obvious and simple as defining factual truth has proven beyond the abilities of some highly skilled and deeply motivated negotiators. So, of course, those who adhere rigidly to preconceived notions automatically remove themselves from dialogue, and I cannot presume to address them here. But for those willing to entertain possibilities following from ideas and methods with which they may be unfamiliar, I say, read on.

What I want to propose differs in several fundamental respects from what has come before, and it is very similar in one fundamental respect. The similarity stems from the realization that essentially the same thing can be authoritatively stated at different times and place by different people using different words and different languages in relation to different customs and traditions. For instance, the versions of the Golden Rule given in the Gospels of Matthew or Luke are conceptually identical with the sentiment expressed in the Hindu Mahabarata, the Confucian Analects, the Jewish Talmud, the Muslim 13th Hadith, and the Buddhist Unada-Varga (http://www.thesynthesizer.org/golden.html; http://philosophy.tamu.edu/~gary/bioethics/ethicaltheory/universalizability.html).

So, rather than defining consensus in terms of strict agreement (with no uncertainty) on the absolute value of various propositions, it should be defined in terms of probabilities of consistent agreement (within a range of uncertainty) on the relative value of various propositions. Instead of evaluating isolated and decontextualized value statements one at a time, I propose evaluating value statements hypothesized to cohere with one another within a larger context together, as a unit.Instead of demanding complete data on a single set of propositions, I propose requiring and demonstrating that the same results be obtained across different sets of propositions addressing the same thing. Instead of applying statistical models of group level inter-variable relations to these data, I propose applying measurement models of individual level within-variable relations. Instead of setting policy on the basis of centrally controlled analytic results that vary incommensurably across data sets I propose setting policy on the basis of decentralized, distributed results collectively produced by networks of individuals whose behaviors and decisions are coordinated and aligned by calibrated instruments measuring in common commensurable units. All of these proposals are described in detail in previous posts here, and in the references included in those posts.

What I’m proposing is rooted in and extends existing practical solutions to the definition and implementation of standards. And though research across a number of fields suggests that a new degree of consensus on some basic issues seems quite possible, that consensus will not be universal and it should not be used as a basis for compelling conformity. Rather, the efficiencies that stand to be gained by capitalizing (literally) on existing but unrecognized standards of behavior and performance are of a magnitude that would easily support generous latitude in allowing poets, nonconformists, and political dissenters to opt out of the system at little or no cost to themselves or anyone else.

That is, as has been described and explained at length in previous posts here, should we succeed in establishing an Intangible Assets Metric System and associated genuine progress indicator or happiness index, we would be in the position of harnessing the power of the profit motive as an economic driver of growth in human, social, and natural capital. Instead of taking mere monetary profits as a measure of improved quality of life, we would set up economic systems in which the measurement and the management of quality of life determines monetary profits. The basic idea is that individual ownership of and accountability for what is, more than anything else, our rightful property–our own abilities, motivations, health, trustworthiness, loyalty, etc.–ought to be a significant factor in promoting the conservation and growth of these forms of capital.

In this context, what then might serve as a practical approach to resolving disputes between those who advocate standards and those who reject them, or between those who trust in our capacity to function satisfactorily as a society without standards and those who do not? Such an approach begins by recognizing the multitude of ways in which all of us rely on standards every day. We do not need to concern ourselves with the technical issues of electronics or manufacturing, though standards are essential here. We do not need even to take up the role of standards as guides to grocery or clothing store purchasing decisions or to planning meetings or travel across time zones.

All we need to think about is something as basic as communication. The alphabet, spelling, pronunciation, and grammatical rules, dictionaries, and educational curricula are all forms of standards that must be accepted, recognized and adhered to before the most basic communication can be achieved. The shapes of various letters or symbols, and the sounds associated with them, are all completely arbitrary. They are conventions that arose over centuries of usage that passed long before the rules were noted, codified, and written down. And spoken languages remain alive, changing in ways that break the rules and cause them to be rewritten, as when new words emerge, or previously incorrect constructions become accepted.

But what is the practical value for a new consensus in recognizing our broad acceptance of linguistic standards? Contrary to the expectations of l’Academie Francaise, for instance, we cannot simply make up new rules and expect people to follow them. No, the point of taking language as a key example goes deeper than that. We noted that usage precedes the formulation of rules, and so it must also be in finding our way to a basis for a new consensus. The question is, what are the lawful patterns by which we already structure behavior and decisions, patterns that might be codified in the language of a social science?

These patterns are being documented in research employing probabilistic measurement models. The fascinating thing about these patterns is that they often retain their characteristic features across different samples of people being measured, across time and space, and across different sets of questions on tests, surveys, or assessments designed to measure the same ability, behavior, attitude, or performance. The stability and constancy of these patterns are such that it appears possible to link all of the instruments measuring the same things to common units of measurement, so that everyone everywhere could think and act together in a common language.

And it is here, in linking instruments together in an Intangible Assets Metric System, that we arrive at a practical way of resolving some disputes between absolutists and relativists. Though we should and will take issue with his demand for certainty, Latour (2005, p. 228) asks the right question, 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!”

Nowhere does Latour show any awareness of what has been accomplished in social research employing probabilistic measurement models, but he nonetheless grasps exactly how the results of that research will not realize its potential unless it is expanded into networks of interconnected instrumentation. He understands that his theory of networked actors coordinated via virtual threads of standardized forms, metrics, vocabularies describes how scientific metrology and standards set the benchmark for universal consensus. Latour stresses that the focus here is on concrete material practices that can be objectively observed and replicated. As he says, when those practices are understood, then you know how to “do the same operation for other less traceable, less materialized circulations” (p. 229).

Latour’s primary concerns are with the constitution of sociology as a science of the social, and with the understanding of the social as networks of actors whose interests are embodied in technical devices that mediate relationships. Throughout his work, he therefore focuses on the description of existing sociotechnical phenomena. Presumably because of his lack of familiarity with social measurement theory and practice, Latour does not speak to ways in which the social sciences could go beyond documenting less traceable and less materialized circulations to creating more traceable and more materialized circulations, ones capable of more closely emulating those found in the natural sciences.

Latour’s results suggest criteria that may show some disputes regarded as unresolvable to have unexplored potentials for negotiation. That potential depends, as Latour says, on calibrating instruments that can be hooked up in a metrological chain in an actual material network with known properties (forms, Internet connections and nodes, a defined unit of measurement with tolerable uncertainty, etc.) and known costs. In the same way that the time cannot be told from a clock disconnected from the chain of connections to the standard time, each individual instrument for measuring abilities, health, quality of life, etc. will also have to be connected to its standard via an unbroken chain.

But however intimidating these problems might be, they are far less imposing than the ignorance that prevents any framing of the relevant issues in the first place. Addressing the need for rigorous measurement in general, Rasch (1980, pp. xx) agreed that “this is a huge challenge, but once the problem has been formulated it does seem possible to meet it.” Naturally enough, the needed work will have to be done by those of us calibrating the instruments of education, health care, sociology, etc. Hence my ongoing involvement in IMEKO, the International Measurement Confederation (http://www.tu-ilmenau.de/fakmb/Home.2382.0.html).

References

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

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.

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Reinventing Capitalism: Diagramming Living Capital Flows in a Green, Sustainable, and Responsible Economy

January 13, 2010

I often make reference to the difference between the currently predominant three-capitals economic model and the emerging green, sustainable, and socially responsible four-capitals model. I also cite my primary sources for this distinction in the work of Paul Ekins and Paul Hawken (see references below), though the basic ideas go back to older work by John Hicks, Irving Fisher, and many others. A picture is worth a thousand words, so it’s about time I took the trouble to explain this vital difference in greater detail, graphically.

The basic issue is that the current state of capitalism is problematic because it is still at an early stage in its development. Capitalism is incomplete. Its fundamental flaws stem less from inherent contradictions than from resolvable ones. The moral fundamentals of capitalism are identical with those forming the basis of meaningful and productive relationships in natural and social ecologies. Profit, for example, is perhaps best understood as nourishment for life (de Geus, 1997; also see Friedman, 2008; Goldberg, 2009; Greider, 2003; Hawken, 1993; Shermer, 2007). This is in fact the point of the emergent field of ecological economics. Thus, as Hawken, Lovins, and Lovins (1999, p. 5) put it,

“Capitalism, as practiced, is a financially profitable, nonsustainable aberration in human development. What might be called ‘industrial capitalism’ does not fully conform to its own accounting principles. It liquidates its capital and calls it income. It neglects to assign any value to the largest stocks of capital it employs–the natural resources and living systems, as well as the social and cultural systems that are the basis of human capital.”

Ekins, Hillman, and Hutchison (1992, p. 49; also see Ekins, 1992; Hawken, Lovins, & Lovins, 1999)  provide a diagram modeling the incomplete three-capitals economic model (see Figure 1). Here we see the narrowly-defined land, labor, and manufactured capital being burned for consumption, utility, and profits, some of which are recycled back into new investments. Waste and inefficiency do not figure into the process enough to be of concern. Profit is defined in terms of whatever the market will bear and the destruction of the capital resource base.

Figure 2 (from Ekins, Hillman, & Hutchison, 1992, p. 61) diagrams the comprehensively-defined four-capitals model. Now we have human, social, natural, and manufactured capital flowing together in a system that includes all of the resources necessary for life, liberty, and the pursuit of happiness. Profit is defined in terms of waste removal and increasingly lean thinking and acting (Hawken, Lovins, & Lovins, 1999, pp. 125, 133). Since all human suffering, sociopolitical discontent, and environmental degradation can be be expressed in terms of waste (Hawken, Lovins, & Lovins, 1999, p. 59), the four-capitals model is a necessary component of any policy platform that focuses on driving sustainable increases in Genuine Progress Indicators or Happiness Indexes (Anielski, 2007; Cameron, 2008).

One of the major themes of this blog is the concept of living capital.  Though human, social, and natural capital literally involve living beings, capital itself must be brought to life before a four-capitals economy can be made workable (Fisher, 2002, 2005, 2009a, 2009b, 2010). Capital is brought to life via measures that (1) scientifically stand for something that adds up in a way that can be meaningfully expressed in numbers and (2) are expressed in univerally uniform and accessible common languages that function as currencies for the exchange of value.

Scientific and financial instruments of all kinds are calibrated in order to tap the flowing current of value in an economy, giving tangible expression to something inherently abstract and intangible. When we can represent capital via scientific measures, it comes alive in the way that its flow is unimpeded by the inefficiencies of so-called measures that do not add up and that are locally dependent on specific instruments (Fisher, 2002, 2007, 2010). Transaction costs, the most important costs in any economy, are dramatically affected by the quality of measurement (Barzel, 1982; Benham & Benham, 2000). The core problem in re-inventing capitalism is figuring out how to bring social and environmental externalities into the market. Measurement will inevitably be of vital concern in solving this problem. Unfortunately, deep, broad and usually unexamined cultural assumptions about the supposed limits of measures made using tests, surveys, and assessments are needlessly  shackling expectations and prolonging dependence on obsolete technologies. See prior posts in this blog and my publications (Fisher, 2000, 2005, 2006, 2007, 2008a, 2008b, 2009a, 2009b, 2010, etc.) for more on the technical opportunities and economics of metrology.

No matter if we’re measuring bushels, barrels, hours, kilowatts, health, motivation, trust, performance, or environmental quality, scientific measurement opens the door to legal and financial means of establishing value and ownership. When our metrics are not scientific, as is the case with the vast majority of measures of human, social, and natural capital, it is nearly impossible to know what we’re getting for our money and to show how much stock of value we hold. It is accordingly also then impossible to manage the economy systematically and responsibly for long term sustainability. We must then build the metrological infrastructure of human, social, and natural capital (Fisher, 2009a, 2009b) in a new extension of the metric system if we are to ever achieve a comprehensive four-capitals economy that effectively re-invents capitalism.

References

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

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Benham, A., & Benham, L. (2000). Measuring the costs of exchange. In C. Ménard (Ed.), Institutions, contracts and organizations: Perspectives from new institutional economics (pp. 367-375). Cheltenham, UK: Edward Elgar.

Cameron, G. (2008, Spring/Summer). Oikos and economy: The Greek legacy in economic thought. PhaenEx, 3(1), 112-33.

de Geus, A. (1997). The living company: Habits for survival in a turbulent business environment (Foreword by Peter M. Senge). Boston, MA: Harvard Business School Press.

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

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

Ekins, P. (2003, March). Identifying critical natural capital: Conclusions about critical natural capital. Ecological Economics, 44(2-3), 277-292.

Ekins, P., Folke, C., & De Groot, R. (2003, March). Identifying critical natural capital. Ecological Economics, 44(2-3), 159-163.

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

Ekins, P., Simon, S., Deutsch, L., Folke, C., & De Groot, R. (2003, March). A framework for the practical application of the concepts of critical natural capital and strong sustainability. Ecological Economics, 44(2-3), 165-185.

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

Fisher, W. P., Jr. (2000). Objectivity in psychosocial measurement: What, why, how. Journal of Outcome Measurement, 4(2), 527-563 [http://www.livingcapitalmetrics.com/images/WP_Fisher_Jr_2000.pdf].

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

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

Fisher, W. P., Jr. (2006). Meaningfulness, sufficiency, invariance, and conjoint additivity. Rasch Measurement Transactions, 20(1), 1053 [http://www.rasch.org/rmt/rmt201.htm].

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. (2008a, March 28). Rasch, Frisch, two Fishers and the prehistory of the Separability Theorem. In  William P. Fisher, Jr. (Chair), Session 67.056. Reading Rasch Closely: The History and Future of Measurement. American Educational Research Association, Rasch Measurement SIG, New York University, New York City [http://www.livingcapitalmetrics.com/images/RaschFisherFrisch.EJHET.pdf].

Fisher, W. P., Jr. (2008b). Vanishing tricks and intellectualist condescension: Measurement, metrology, and the advancement of science. Rasch Measurement Transactions, 21(3), 1118-1121 [http://www.rasch.org/rmt/rmt213c.htm].

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

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

Fisher, W. P., Jr. (2010). 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.

Friedman, D. (2008). Morals and markets: An evolutionary account of the modern world. Palgrave Macmillan.

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

Greider, W. (2003). The soul of capitalism: Opening paths to a moral economy. New York: Simon & Schuster.

Hawken, P. (1993). The ecology of commerce: A declaration of sustainability. New York: HarperCollins Publishers.

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

Korten, D. (2009). Agenda for a new economy: From phantom wealth to real wealth. San Francisco: Berret-Koehler Publishing.

Shermer, M. (2007). The mind of the market: Compassionate apes, competitive humans, and other tales from evolutionary economics. New York: Times Books.

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