Posts Tagged ‘science’

Psychology and the social sciences: An atheoretical, scattered, and disconnected body of research

February 16, 2019

A new article in Nature Human Behaviour (NHB) points toward the need for better theory and more rigorous mathematical models in psychology and the social sciences (Muthukrishna & Henrich, 2019). The authors rightly say that the lack of an overarching cumulative theoretical framework makes it very difficult to see whether new results fit well with previous work, or if something surprising has come to light. Mathematical models are especially emphasized as being of value in specifying clear and precise expectations.

The point that the social sciences and psychology need better theories and models is painfully obvious. But there are in fact thousands of published studies and practical real world applications that not only provide, but indeed often surpass, the kinds of predictive theories and mathematical models called for in the NHB article. The article not only makes no mention of any of this work, its argument is framed entirely in a statistical context instead of the more appropriate context of measurement science.

The concept of reliability provides an excellent point of entry. Most behavioral scientists think of reliability statistically, as a coefficient with a positive numeric value usually between 0.00 and 1.00. The tangible sense of reliability as indicating exactly how predictable an outcome is does not usually figure in most researchers’ thinking. But that sense of the specific predictability of results has been the focus of attention in social and psychological measurement science for decades.

For instance, the measurement of time is reliable in the sense that the position of the sun relative to the earth can be precisely predicted from geographic location, the time of day, and the day of the year. The numbers and words assigned to noon time are closely associated with the Sun being at the high point in the sky (though there are political variations by season and location across time zones).

That kind of a reproducible association is rarely sought in psychology and the social sciences, but it is far from nonexistent. One can discern different degrees to which that kind of association is included in models of measured constructs. Though most behavioral research doesn’t mention the connection between linear amounts of a measured phenomenon and a reproducible numeric representation of it (level 0), quite a significant body of work focuses on that connection (level 1). The disappointing thing about that level 1 work is that the relentless obsession with statistical methods prevents most researchers from connecting a reproducible quantity with a single expression of it in a standard unit, and with an associated uncertainty term (level 2). That is, level 1 researchers conceive measurement in statistical terms, as a product of data analysis. Even when results across data sets are highly correlated and could be equated to a common metric, level 1 researchers do not leverage that source of potential value for simplified communication and accumulated comparability.

And then, for their part, level 2 researchers usually do not articulate theories about the measured constructs, by augmenting the mathematical data model with an explanatory model predicting variation (level 3). Level 2 researchers are empirically grounded in data, and can expand their network of measures only by gathering more data and analyzing it in ways that bring it into their standard unit’s frame of reference.

Level 3 researchers, however, have come to see what makes their measures tick. They understand the mechanisms that make their questions vary. They can write new questions to their theoretical specifications, test those questions by asking them of a relevant sample, and produce the predicted calibrations. For instance, reading comprehension is well established to be a function of the difference between a person’s reading ability and the complexity of the text they encounter (see articles by Stenner in the list below). We have built our entire educational system around this idea, as we deliberately introduce children first to the alphabet, then to the most common words, then to short sentences, and then to ever longer and more complicated text. But stating the construct model, testing it against data, calibrating a unit to which all tests and measures can be traced, and connecting together all the books, articles, tests, curricula, and students is a process that began (in English and Spanish) only in the 1980s. The process still is far from finished, and most reading research still does not use the common metric.

In this kind of theory-informed context, new items can be automatically generated on the fly at the point of measurement. Those items and inferences made from them are validated by the consistency of the responses and the associated expression of the expected probability of success, agreement, etc. The expense of constant data gathering and analysis can be cut to a very small fraction of what it is at levels 0-2.

Level 3 research methods are not widely known or used, but they are not new. They are gaining traction as their use by national metrology institutes globally grows. As high profile critiques of social and psychological research practices continue to emerge, perhaps more attention will be paid to this important body of work. A few key references are provided below, and virtually every post in this blog pertains to these issues.

References

Baghaei, P. (2008). The Rasch model as a construct validation tool. Rasch Measurement Transactions, 22(1), 1145-6 [http://www.rasch.org/rmt/rmt221a.htm].

Bergstrom, B. A., & Lunz, M. E. (1994). The equivalence of Rasch item calibrations and ability estimates across modes of administration. In M. Wilson (Ed.), Objective measurement: Theory into practice, Vol. 2 (pp. 122-128). Norwood, New Jersey: Ablex.

Cano, S., Pendrill, L., Barbic, S., & Fisher, W. P., Jr. (2018). Patient-centred outcome metrology for healthcare decision-making. Journal of Physics: Conference Series, 1044, 012057.

Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Measurement & Evaluation in Counseling & Development, 43(2), 121-149.

Embretson, S. E. (2010). Measuring psychological constructs: Advances in model-based approaches. Washington, DC: American Psychological Association.

Fischer, G. H. (1973). The linear logistic test model as an instrument in educational research. Acta Psychologica, 37, 359-374.

Fischer, G. H. (1983). Logistic latent trait models with linear constraints. Psychometrika, 48(1), 3-26.

Fisher, W. P., Jr. (1992). Reliability statistics. Rasch Measurement Transactions, 6(3), 238 [http://www.rasch.org/rmt/rmt63i.htm].

Fisher, W. P., Jr. (2008). The cash value of reliability. Rasch Measurement Transactions, 22(1), 1160-1163 [http://www.rasch.org/rmt/rmt221.pdf].

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

Green, S. B., Lissitz, R. W., & Mulaik, S. A. (1977). Limitations of coefficient alpha as an index of test unidimensionality. Educational and Psychological Measurement, 37(4), 827-833.

Hattie, J. (1985). Methodology review: Assessing unidimensionality of tests and items. Applied Psychological Measurement, 9(2), 139-64.

Hobart, J. C., Cano, S. J., Zajicek, J. P., & Thompson, A. J. (2007). Rating scales as outcome measures for clinical trials in neurology: Problems, solutions, and recommendations. Lancet Neurology, 6, 1094-1105.

Irvine, S. H., Dunn, P. L., & Anderson, J. D. (1990). Towards a theory of algorithm-determined cognitive test construction. British Journal of Psychology, 81, 173-195.

Kline, T. L., Schmidt, K. M., & Bowles, R. P. (2006). Using LinLog and FACETS to model item components in the LLTM. Journal of Applied Measurement, 7(1), 74-91.

Lunz, M. E., & Linacre, J. M. (2010). Reliability of performance examinations: Revisited. In M. Garner, G. Engelhard, Jr., W. P. Fisher, Jr. & M. Wilson (Eds.), Advances in Rasch Measurement, Vol. 1 (pp. 328-341). Maple Grove, MN: JAM Press.

Mari, L., & Wilson, M. (2014). An introduction to the Rasch measurement approach for metrologists. Measurement, 51, 315-327.

Markward, N. J., & Fisher, W. P., Jr. (2004). Calibrating the genome. Journal of Applied Measurement, 5(2), 129-141.

Maul, A., Mari, L., Torres Irribarra, D., & Wilson, M. (2018). The quality of measurement results in terms of the structural features of the measurement process. Measurement, 116, 611-620.

Muthukrishna, M., & Henrich, J. (2019). A problem in theory. Nature Human Behaviour, 1-9.

Obiekwe, J. C. (1999, August 1). Application and validation of the linear logistic test model for item difficulty prediction in the context of mathematics problems. Dissertation Abstracts International: Section B: The Sciences & Engineering, 60(2-B), 0851.

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

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

Pendrill, L., & Petersson, N. (2016). Metrology of human-based and other qualitative measurements. Measurement Science and Technology, 27(9), 094003.

Sijtsma, K. (2009). Correcting fallacies in validity, reliability, and classification. International Journal of Testing, 8(3), 167-194.

Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107-120.

Stenner, A. J. (2001). The necessity of construct theory. Rasch Measurement Transactions, 15(1), 804-5 [http://www.rasch.org/rmt/rmt151q.htm].

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.

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

Stenner, A. J., Stone, M. H., & Fisher, W. P., Jr. (2018). The unreasonable effectiveness of theory based instrument calibration in the natural sciences: What can the social sciences learn? Journal of Physics Conference Series, 1044(012070).

Stone, M. H. (2003). Substantive scale construction. Journal of Applied Measurement, 4(3), 282-297.

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.

Wright, B. D., & Stone, M. H. (1979). Chapter 5: Constructing a variable. In Best test design: Rasch measurement (pp. 83-128). Chicago, Illinois: MESA Press.

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

Wright, B. D., Stone, M., & Enos, M. (2000). The evolution of meaning in practice. Rasch Measurement Transactions, 14(1), 736 [http://www.rasch.org/rmt/rmt141g.htm].

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

February 2, 2019

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

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

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

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

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

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

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Why economic growth can and inevitably will be green

October 1, 2018

So, approaching matters once again from yet another point of view, we have Jason Hickel explaining a couple of weeks ago “Why Growth Can’t Be Green.” This article provides yet another example of how the problem is the problem. That is, the way we define problems sets up particular kinds of solutions in advance, and sometimes, as Einstein famously pointed out, problems cannot be solved from within the same conceptual framework that gave rise to them. I’ve expanded on this theme in a number of previous posts, for instance, here.

Hickel takes up the apparent impossibility of aligning economic growth with environmental values. He speaks directly to what he calls the rebound effect, the way that “improvements in resource efficiency drive down prices and cause demand to rise—thus canceling out some of the gains.” But that rebound can happen only as long as the economy remains defined and limited by the alignment of manufactured capital and finance, ignoring the largely unexamined and unconsidered possibility that human, social, and natural capital could be measured well enough to be also aligned with finance.

Hence, as I say, the problem is the problem. Broadening one’s conceptualization of the problem opens up new opportunities that otherwise never come into view.

The Hickel article’s entire focus is then on top-down policy impositions like taxes or a Genuine Progress Index. These presume human, social, and natural capital can only ever exist in dead formations that have to be micromanaged and concretely manipulated, and that efficient markets bringing them to life are inherently and literally unthinkable. (See a short article here for an explanation of the difference between dead and living capital. There’s a lot more where that came from, as is apparent in the previous posts here in this blog.)

The situation could be vastly different than what Hickel imagines. If we could own, buy, and sell products in efficient markets we could reward the production of human, social, and environmental value. In that scenario, when improvements in environmental resource efficiency are obtained, demand for that new environmental value will rise and its price will go down, not the resource’s price.

We ought to be creative enough to figure out how to configure markets so that prices for environmental resources (oil, farmland, metals, etc.) can stay constant or fall without increasing demand for them, as could happen if that demand is counterbalanced and absorbed by rising human, social, and environmental quality capital values.

The question is how to absorb the rebound effect in other forms of capital that grow in demand while holding demand for the natural resource base in check. The vital conceptual distinction is between socialistic centralized planning and control of actual physical entities (people, communities, the environment, and manufactured items), on the one hand, and capitalistic decentralized distributed network effects on abstract transferable representations, on the other. Everyone defaults to the socialist scenario without ever considering there might be a whole other arena in which fruitful possibilities might be imagined.

What if, for instance, we could harness the profit motive to promote growth in genuine human, social, and environmental value? What if we were able to achieve qualitatively meaningful increases in authentic wealth that were economically contingent on reduced natural resource consumption? What if the financial and substantive value profits that could be had meant that resource consumption could be reduced by the same kinds of factors as have been realized in the context of Moore’s Law? What if a human economics of genuine value could actually result in humanity being able to adjust the global thermostat up or down in small increments by efficiently rewarding just the right combinations of policies and practices at the right times and places in the right volumes?

The only way that could ever happen is if people are motivated to do the right thing for the earth and for humanity because it is the right thing for them and their families. They have to be able to own their personal shares of their personal stocks of human, social, and natural capital. They have to be able to profit from investments in their own and others’ shares. They will not act on behalf of the earth and humanity only because it is the right thing to do. There has to be evidence and explanations of how everyone is fairly held accountable to the same standards, and has the same opportunities for profit and loss as anyone else. Then, and only then, it seems, will human, social, and environmental value become communicable in a viral contagion of good will.

Socialism has been conclusively proven unworkable, for people, communities, and the environment, as well as financially. But a human, social, and natural capitalism has hardly even been articulated, much less tried out. How do we make human, social, and natural capital fungible? How might the economy transcend its traditional boundaries and expand itself beyond the existing alignment of manufactured capital and finance?

It’s an incredibly complex proposal, but also seems like such a simple thing. The manufactured capital economy uses the common language of good measurement to improve quality, to simplify management communications, and to lower transaction costs in efficient markets. So what should we do if we want to correct the imbalanced negative impacts on people, communities, and the environment created by the misplaced emphasis on aligning only manufactured capital and financial capital?

As has been repeatedly proposed for years in this blog, maybe we should use the manufactured capital markets as a model and use good measurement to improve the quality of human, social, and environmental capital, to simplify communications and management, to lower transaction costs, and to align the genuine human, social, and environmental value created with financial value in efficient markets.

Of course, grasping that as viable, feasible, and desirable requires understanding that substantively meaningful precision measurement is something quite different from what usually passes for quantification. And that is an entirely different story, though one taken up repeatedly in previous entries in this blog, of course….

 

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Self-Sustaining Sustainability, Once Again, Already

August 12, 2018

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

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

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

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

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

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

Self-Sustaining Sustainability

Relevant Information Resources

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

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

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

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

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

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

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

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

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

Fisher, W. P., Jr. (2009, November 19). Draft legislation on development and adoption of an intangible assets metric system. Living Capital Metrics blog: https://livingcapitalmetrics.wordpress.com/2009/11/19/draft-legislation/.

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

Fisher, W. P., Jr. (2009). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (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, 22 November). Meaningfulness, measurement, value seeking, and the corporate objective function: An introduction to new possibilities. LivingCapitalMetrics.com, Sausalito, California.

Fisher, W. P., Jr. (2010). Measurement, reduced transaction costs, and the ethics of efficient markets for human, social, and natural capital. Bridge to Business Postdoctoral Certification, Freeman School of Business, Tulane University (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2340674).

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

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

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

Fisher, W. P., Jr. (2012). What the world needs now: A bold plan for new standards [Third place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1 & 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2015). A probabilistic model of the law of supply and demand. Rasch Measurement Transactions, 29(1), 1508-1511 [http://www.rasch.org/rmt/rmt291.pdf].

Fisher, W. P., Jr. (2015). Rasch measurement as a basis for metrologically traceable standards. Rasch Measurement Transactions, 28(4), 1492-1493 [http://www.rasch.org/rmt/rmt284.pdf].

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

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

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

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

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

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

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

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

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

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

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

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

 

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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.

Self-Sustaining Sustainability

August 6, 2018

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

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

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

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

Q: How do we do that?

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

Q: How do we do that?

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

Q: How do we do that?

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

Q: How could that be done?

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

Q: What does that take?

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

Q: Can that be done?

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

Q: How do we start?

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

Q: It sounds like an iterative process.

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

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

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

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

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

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

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

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

 

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LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
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Economy of language, Eros, meaning, the public, and its problems

July 11, 2017

The medium is the message. The more transparent the medium is, the more seductive the messages expressed in it. The seductiveness of numbers stems from their roots in the mathematical quality of all thinking: the way that signs are used as the media of concept-thing relations. Our captivation with numbers is entirely embedded in the allure of language, which stems in large part from its economy: knowing how to read, write, speak, and listen saves us the trouble of re-inventing words and concepts for ourselves, and of having to translate each other’s private languages. The problem is, of course, that having words for things and sharing them by no means assures understanding. But when it works, it really works, as the history of science shows.

Seductive enthrallment with meaning and beauty defines the parameters of the difference between the modern Cartesian dualist world view and the emerging unmodern nondualist world view. This is the whole point of taking up Heidegger’s sense of method as meta-odos. As Plato saw, Socrates’ recounting of the myth of Eros told to him by Diotima conveys how captivation with beauty embodies the opposites of wealth and poverty in a simultaneous possession and absence, neither of which is ever complete.

The evolutionary/developmental paradigm shift taking place will transform everything by institutionalizing in every area of life an order of magnitude increase in the complexity of relationships, and a corresponding increase in the simplicity with which those relationships can be managed. The compelling absorption into the flow of meaning that necessarily informs discourse but currently functions as an unacknowledged assumption informing operations will itself be brought into view and will become an object of operations.

As Dewey understood, public consciousness of an issue or set of issues, and the will to take them on, emerges when existing institutions fail. We are certainly living in a time in which our political, economic, social, educational, medical, legal, environmental, etc. institutions have been failing to live up to their responsibilities for quite a number of years. The efforts of the public to address these failures have been obstructed by the lack of the media needed for integrating the complex, multilevel, and discontinuous opposites of harmony and dissonance, agreement and dissent, that structure a binding, coherent culture.

Science is nothing but an extension of everyday reasoning. Instead of imitating the natural sciences, the social sciences need to focus on how science extends the complex cognitive ecologies of language. As we figure that out and get these metasystems in place, we will simultaneously create the media the public needs to find its voice and organize itself to meet the challenges of how to build new institutions capable of successfully countering human suffering, social discontent, and environmental degradation.

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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.

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.

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.

Measuring/Managing Social Value

August 28, 2012

From my December 1, 2008 personal journal, written not long after the October 2008 SoCap conference. I’ve updated a few things that have changed in the intervening years.

Over the last month, I’ve been digesting what I learned at the Social Capital Markets conference at Fort Mason in San Francisco, and at the conference I attended just afterward, Bioneers, in Marin county. Bioneers (www.Bioneers.org) could be called Natural Capital Markets. It was quite like the Social Capital Markets conference with only a slight shift in emphasis, and lots of discussion of social value.

The main thing that impressed me at both of these conferences, apart from what I already knew about the caring passion I share with so many, is the huge contrast between that passion and the quality of the data that so many are basing major decisions on. Seeing this made me step back and think harder about how to shape my message.

First, though it may not seem like it initially, there is incredible practical value to be gained from taking the trouble to construct good measures. We do indeed manage what we measure. So whatever we measure becomes what we manage. If we’re not measuring anything that has anything to do with our mission, vision, or values, then what we’re managing won’t have anything to do with those, either. And when the numbers we use as measures do not actually represent a constant unit amount that adds up the way the numbers do, then we don’t have a clue what we’re measuring and we could be managing just about anything.

This is not the way to proceed. First take-away: ask for more from your data. Don’t let it mislead you with superficial appearances. Dig deeper.

Second, to put it a little differently, percentages, scores, and counts per capita, etc. are not measures that have the same meaning or quality that measures of height, weight, time, temperature, or volts have. However, for over 50 years, we have been constructing measures mathematically equivalent to physical measures from ability tests, surveys, assessments, checklists, etc. The technical literature on this is widely available. The methods have been mainstream at ETS, ACT, state and national departments of education globally, etc for decades.

Second take-away: did I say you should ask for more from your data? You can get it. A lot of people already are, though I don’t think they’re asking for nearly as much as they could get.

Third, though the massive numbers of percentages, scores, and counts per capita are not the measures we seek, they are indeed exactly the right place to start. I have seen over and over again, in education, health care, sociology, human resource management, and most recently in the UN Millennium Development Goals data, that people do know exactly what data will form a proper basis for the measurement systems they need.

Third take-away: (one more time!) ask for more from your data. It may conceal a wealth beyond what you ever guessed.

So what are we talking about? There are methods for creating measures that give you numbers that verifiably stand for a substantive unit amount that adds up in the same way one-inch blocks do (probabilistically, and within a range of error). If the instrument is properly calibrated and administered, the unit size and meaning will not change across individuals or samples measured. You can reduce data volume dramatically, not only with no loss of information but also with false appearances of information either indicated as error or flagged for further attention. You can calibrate a continuum of less to more that is reliably and reproducibly associated with, annotated by, and interpreted through your own indicators. You can equate different collections of indicators that measure the same thing so that they do so in the same unit.

Different agencies using the same, different, or mixed collections of indicators in different countries or regions could assess their measures for comparability, and if they are of satisfactory quality, equate them so they measure in the same unit. That is, well-designed instruments written and administered in different languages routinely have their items calibrate in the same order and positions, giving the same meaning to the same unit of measurement. For instance, see the recent issue of the Journal of Applied Measurement ([link]) devoted to reports on the OECD’s Programme for International Student Assessment.

This is not a data analysis strategy. It is an instrument calibration strategy. Once calibrated, the instrument can be deployed. We need to monitor its structure, but the point is to create a tool people can take out into the world and use like a thermometer or clock.

I’ve just been looking at the Charity Navigator (for instance, [link]) and the UN’s Millenium Development Goals ([link]), and the databases that have been assembled as measures of progress toward these goals ([link]). I would suppose these web sites show data in forms that people are generally familiar with, so I’m working up analyses to use as teaching tools from the UN data.

You don’t have to take any of this at my word. It’s been documented ad nauseum in the academic literature for decades. Those interested can find out more than they ever wanted to know at http://www.Rasch.org, in the Wikipedia Rasch entry, in the articles and books at JAMPress.com, or in dozens of academic journals and hundreds of books. Though I’ve done my share of it, I’m less interested in continuing to add to that than I am in making a tangible contribution to improving people’s lives.

Sorry to go on like this. I meant to keep this short. Anyway, there it is.

PS, for real geeks: For those of you serious about learning about measurement as it is rigorously and mathematically defined, look into taking Everett Smith’s measurement course at Statistics.com ([link]) or David Andrich’s academic units at the University of Western Australia ([link]). Available software includes Mike Linacre’s Winsteps, Andrich’s RUMM, and Mark Wilson’s, at UC Berkeley, Conquest.

The methods Ev, Mike, David, and Mark teach have repeatedly been proven, both in mathematical theory and in real life, to be both necessary and sufficient in the construction of meaningful, practical measurement. Any number of ways of defining objectivity in measurement have been shown to reduce to the mathematical models they use. Why all the Chicago stuff? Because of Ben Wright. I’m helping (again) to organize a conference in his honor, to be held in Chicago next March. His work won him a Career Achievement Award from the Association of Test Publishers, and the coming conference will celebrate his foundational contributions to computerized measurement in health care.

As a final note, for those of you fearing reductionistic meaninglessness, look into my philosophical work.  But enough…

Proposed U.S. Presidential Candidate Stump Speech

December 29, 2011

Over the course of our history, we have gotten a lot of things right in this country. Our political and economic principles and practices, not to speak of our technological innovations, have been models for countries the world over. The rest of the world has looked to us for leadership for a long time, and continues to do so.

Though some say our day in the sun might be over, I say we’ve hardly begun. We have new things to show the world. The problems we are facing as a nation right now have not come about because of flaws or failings in our basic principles. Those problems have come about because we have not yet creatively applied those principles in new ways, in new areas of our lives.

We have built our democracy and our economy on the ideas of equal rights and fair play, so that everyone has a chance to get into the game and make a place for themselves. Because of the way we have invested in these ideas over the last 235 years, this country has made big gains in bringing higher standards of living to more and more of our citizens, and to the citizens of countries on every continent. Along the way, there have been times when we’ve stumbled, but we’ve always picked ourselves back up and moved on to reach even higher standards than before.

We’ve been stumbling again here over these last few years. Though we continue to succeed with creative and innovative ideas in some areas, the world is changing. It isn’t enough for us to just react to the changes going on around us, or to resist those changes. We need to initiate changes of our own. Creating the future lets us predict it, lets us own it. Let me tell you about my vision of how we can create a new future together, a future that we can all own a piece of.

We have known for a long time that the richness of our lives depends on far more than the mere accumulation of material things. But despite that, the ongoing economic crisis has come about in large part precisely because we systematically put too much weight on material things in gauging our quality of life. But real wealth–and we all know this–the things that really make life worth living are not measured by any of the numbers that appear in the financial pages’ stock and economic indexes.

So efforts have been made to come up with numbers that will rise and fall with changes in our overall quality of life. New measures of real wealth, genuine progress, or happiness have been proposed. Many of us invest our retirement funds in stock indexes tied to socially responsible or environmentally sustainable corporate behaviors.

These are all steps in the right direction. But they fall short of what we need. More importantly, they fall short of what’s possible, and what’s already proven. Advances made in the social sciences over the last 50 years and more are setting the stage for a whole new array of exciting opportunities. It’s time to move these developments out of the lab and bring them to market. For instance, instead of relying on traditional statistics summarizing what’s going on at a high level, we need new measures that help us individually manage our investments in our own resources.

We say we manage what we measure, but, as I’ve already noted, we don’t have systems for measuring what’s really important in life. Are our skills, health, trustworthiness, and environmental quality really as important to us as we say they are? It would be natural to think, if they are that important, we would know how much of each of them we have and what they are worth. We ought to have ways of measuring these things, showing how much we each own, and knowing what it’s all worth. But we don’t.

Without those measures, we can’t effectively manage our own stocks of the resources most valuable to the quality of our lives. If we don’t know where we stand relative to one another or relative to where we were last week or last year, then we lack information vital to knowing how to move forward. And if we don’t know as individuals how to move forward, then we don’t know as a nation. If we do know as individuals where we stand and how to move forward, then we will also know as communities, and as managers in firms, classrooms, clinics, and hospitals.

The role of government in our lives is supposed to be to make things easier. And so to make it easier for everyone to manage the full range of the resources they have available to them, I now propose a new array of initiatives to be undertaken by the National Science Foundation, the National Institute for Standards and Technology, and the National Institutes of Health. These initiatives will focus on the research and education programs we need to create a new set of measurement standards, a kind of metric system that will give us the meaningful and precise numbers we need to manage the sources of our real wealth.

I will furthermore propose new legislation establishing an Intangible Assets Metric System as the legally binding terms for expressing the sources of real wealth in our lives. This law, when passed, as I’m sure it will be, will also establish each individual’s right to the free and clear ownership of their shares of human, social, and natural capital. Nothing is more important to the future of our nation, morally and economically, than each of us having a clear understanding of the value and worth of our reading, writing and math abilities, our health, our social relationships, and our environmental quality.

My administration will also reach out to industries and standards organizations of all kinds, but especially in economics, finance and accounting, to seek new creative ways for applying these measurement standards in managing our resources. I will also implement a new executive order establishing a wide range of new economic incentives designed to encourage investment in information systems for managing the new metrics in personalized accounts.

This series of initiatives will enable us to harmonize our efforts in new ways. We all know we can accomplish more working together as a team than we can alone. A new system of scientific, legal, and financial tools for managing our real wealth will make us a better team than ever. With these tools we will once again assert our leadership as innovators on a global scale, keeping the dream of a better life alive.

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For more on the science behind these ideas, and their potential applications, see previous posts in this blog, and the following:

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.

Fisher, W. P., Jr. (2009, 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. (2009). 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, 30 September). Distinguishing between consistency and error in reliability coefficients: Improving the estimation and interpretation of information on measurement precision. LivingCapitalMetrics.com, Sausalito, California. Social Science Research Network [Online]. Available: http://ssrn.com/abstract=1685556 .

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

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. (2010). Statistics and measurement: Clarifying the differences. Rasch Measurement Transactions, 23(4), 1229-1230 [http://www.rasch.org/rmt/rmt234.pdf].

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

Fisher, W. P., Jr. (2011). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN millennium development goals project. LivingCapitalMetrics.com, Sausalito, California. Social Science Research Network [Online]. (http://ssrn.com/abstract=1739386).

Fisher, W. P., Jr. (2011). Stochastic and historical resonances of the unit in physics and psychometrics. Measurement: Interdisciplinary Research & Perspectives, 9, 46-50.

Fisher, W. P., Jr. (2012). 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 (in press). New York: Palgrave Macmillan.

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

Fisher, W. P., Jr., & Burton, E. (2010). Embedding measurement within existing computerized data systems: Scaling clinical laboratory and medical records heart failure data to predict ICU admission. Journal of Applied Measurement, 11(2), 271-287.

Fisher, W. P., Jr., Elbaum, B., & Coulter, W. A. (2012). Construction and validation of two parent-report scales for the evaluation of early intervention programs. Journal of Applied Measurement, 13, in press.

Fisher, W. P., Jr., Eubanks, R. L., & Marier, R. L. (1997). Equating the MOS SF36 and the LSU HSI physical functioning scales. Journal of Outcome Measurement, 1(4), 329-362.

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., & Karabatsos, G. (2005). Fundamental measurement for the MEPS and CAHPS quality of care scales. In N. Bezruczko (Ed.), Rasch measurement in the health sciences (pp. 373-410). Maple Grove, MN: JAM Press.

Fisher, W. P., Jr., & Stenner, A. J. (2011). Geometric and algebraic formulations of scientific laws: Mathematical principles for phenomenology. Journal of Phenomenological Psychology, in review.

Fisher, W. P., Jr., & Stenner, A. J. (2011, April). Integrating qualitative and quantitative research approaches via the phenomenological method. International Journal of Multiple Research Approaches, 5(1), 89-103.

Fisher, W. P., Jr., & Stenner, A. J. (2011). Making clear what something is:  Scientific law, construct validity and reliability in measuring reading ability. Psychological Methods, in review.

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). 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., & Wright, B. D. (Eds.). (1994). Applications of probabilistic conjoint measurement (Special Issue). International Journal of Educational Research, 21(6), 557-664.

Heinemann, A. W., Fisher, W. P., Jr., & Gershon, R. (2006). Improving health care quality with outcomes management. Journal of Prosthetics and Orthotics, 18(1), 46-50 [http://www.oandp.org/jpo/library/2006_01S_046.asp] .

Solloway, S., & Fisher, W. P., Jr. (2007). Mindfulness in measurement: Reconsidering the measurable in mindfulness. International Journal of Transpersonal Studies, 26, 58-81 [http://www.transpersonalstudies.org/volume_26_2007.html].

Sumner, J., & Fisher, W. P., Jr. (2008). The moral construct of caring in nursing as communicative action: The theory and practice of a caring science. Advances in Nursing Science, 31(4), E19-E36.

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