Archive for the ‘metrology’ Category

IMEKO Joint Symposium in St. Petersburg, Russia, 2-5 July 2019

June 26, 2019

The IMEKO Joint Symposium will be next week, 2-5 July, at the Original Sokos Hotel Olympia Garden, located at Batayskiy Pereulok, 3А, in St. Petersburg, Russia. Kudos to Kseniia Sapozhnikova, Giovanni Rossi, Eric Benoit, and the organizing committee for putting together such an impressive program, which is posted at: https://imeko19-spb.org/wp-content/uploads/2019/06/Program-of-the-Symposium.pdf

Presentations on measurement across the sciences from metrology engineers and psychometricians from around the world will include: Andrich, Cavanagh, Fitkov-Norris, Huang, Mari, Melin, Nguyen, Oon, Powers, Salzberger, Wilson, and multiple other co-authors, including Adams, Cano, Maul, Pendrill, and more.

For background on this rapidly developing new conversation on measurement across the sciences, see the references listed at bottom below. The late Ludwig Finkelstein, editor of IMEKO’s Measurement journal from 1982 to 2000, was a primary instigator of work in this area. At the 2010 Joint Symposium he co-hosted in London, Finkelstein said: “It is increasingly recognised that the wide range and diverse applications of measurement are based on common logical and philosophical principles and share common problems” (Finkelstein, 2010, p. 2). The IMEKO Joint Symposium continues to advance in the direction foreseen by Finkelstein.

Topics to be addressed include a round table discussion on the topic “Terminology issues related to expanding boundaries of measurements” chaired by Mari and Chunovkina.

Paper titles include:

Andrich on “Exemplifying natural science measurement in the social sciences with Rasch measurement theory”

Benoit, et al. on “Musical instruments for the measurement of autism sensory disorders”

Budylina and Danilov on “Methods to ensure the reliability of measurements in the age of Industry 4.0”

Cavanagh, Asano-Cavanagh, and Fisher on “Natural semantic metalanguage as an approach to measuring meaning”

Crenna and Rossi on “Squat biomechanics in weightlifting: Foot attitude effects”

Fisher, Pendrill, Lips da Cruz, and Felin on “Why metrology? Fair dealing and efficient markets for the UN SDGs”

Fisher and Wilson on “The BEAR Assessment System Software as a platform for developing and applying UN SDG metrics”

Fitkov-Norris and Yeghiazarian on “Is context the hidden spanner in the works of educational measurement: Exploring the impact of context on mode of learning preferences”

Gavrilenkov, et al. on “Multicriteria approach to design of strain gauge force transducers”

Grednovskaya, et al. on “Measuring non-physical quantities in the procedures of philosophical practice”

Huang, Oon, and Fisher on “Coherence in measuring student evaluation of teaching: A new paradigm”

Katkov on “The status of and prospects for development of voltage quantum standards”

Kneller and Fayans on “Solving interdisciplinary tasks: The challenge and the ways to surmount it”

Kostromina and Gnedykh on “Problems and prospects of complex psychological phenomena measurement”

Lips da Cruz, Fisher, Pendrill, and Felin on “Accelerating the realization of the UN SDGs through metrological multi-stakeholder interoperability”

Lyubimtsev, et al. on “Measuring systems designed for working with living organisms as biosensors: Features of their metrological maintenance”

Mari, Chunovkina, and Ehrlich on “The complex concept of quantity in the past and (possibly) the future of the International Vocabulary of Metrology”

Mari, Maul, and Wilson on “Can there be one meaning of ‘measurement’ across the sciences?”

Melin, Pendrill, Cano, and the EMPIR NeuroMET 15HLT04 Consortium on “Towards patient-centred cognition metrics”

Morrison and Fisher on “Measuring for management in Science, Technology, Engineering, and Mathematics learning ecosystems”

Nguyen on “The feasibility of using an international common reading progression to measure reading across languages: A case study of the Vietnamese language”

Nguyen, Nguyen, and Adams on “Assessment of the generic problem-solving construct across different contexts”

Oon, Hoi-Ka, and Fisher on “Metrologically coherent assessment for learning: What, why, and how”

Pandurevic, et al. on “Methods for quantitative evaluation of force and technique in competitive sport climbing”

Pavese on “Musing on extreme quantity values in physics and the problem of removing infinity”

Powers and Fisher on “Advances in modelling visual symptoms and visual skills”

Salzberger, Cano, et al. on “Addressing traceability in social measurement: Establishing a common metric for dependence”

Sapozhnikova, et al. on “Music and growl of a lion: Anything in common? Measurement model optimized with the help of AI will answer”

Soratto, Nunes, and Cassol on “Legal metrological verification in health area in Brazil”

Wilson and Dulhunty on “Interpreting the relationship between item difficulty and DIF: Examples from educational testing”

Wilson, Mari, and Maul on “The status of the concept of reference object in measurement in the human sciences compared to the physical sciences”

Background References

Finkelstein, L. (1975). Representation by symbol systems as an extension of the concept of measurement. Kybernetes, 4(4), 215-223.Finkelstein, L. (2003, July). Widely, strongly and weakly defined measurement. Measurement, 34(1), 39-48(10).

Finkelstein, L. (2005). Problems of measurement in soft systems. Measurement, 38(4), 267-274.

Finkelstein, L. (2009). Widely-defined measurement–An analysis of challenges. Measurement: Concerning Foundational Concepts of Measurement Special Issue Section (L. Finkelstein, Ed.), 42(9), 1270-1277.

Finkelstein, L. (2010). Measurement and instrumentation science and technology-the educational challenges. Journal of Physics Conference Series, 238, doi:10.1088/1742-6596/238/1/012001.

Fisher, W. P., Jr. (2009). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement: Concerning Foundational Concepts of Measurement Special Issue (L. Finkelstein, Ed.), 42(9), 1278-1287.

Mari, L. (2000). Beyond the representational viewpoint: A new formalization of measurement. Measurement, 27, 71-84.

Mari, L., Maul, A., Irribara, D. T., & Wilson, M. (2016, March). Quantities, quantification, and the necessary and sufficient conditions for measurement. Measurement, 100, 115-121. Retrieved from http://www.sciencedirect.com/science/article/pii/S0263224116307497

Mari, L., & Wilson, M. (2014, May). An introduction to the Rasch measurement approach for metrologists. Measurement, 51, 315-327. Retrieved from http://www.sciencedirect.com/science/article/pii/S0263224114000645

Pendrill, L. (2014, December). Man as a measurement instrument [Special Feature]. NCSLi Measure: The Journal of Measurement Science, 9(4), 22-33. Retrieved from http://www.tandfonline.com/doi/abs/10.1080/19315775.2014.11721702

Pendrill, L., & Fisher, W. P., Jr. (2015). Counting and quantification: Comparing psychometric and metrological perspectives on visual perceptions of number. Measurement, 71, 46-55. doi: http://dx.doi.org/10.1016/j.measurement.2015.04.010

Pendrill, L., & Petersson, N. (2016). Metrology of human-based and other qualitative measurements. Measurement Science and Technology, 27(9), 094003. Retrieved from https://doi.org/10.1088/0957-0233/27/9/094003

Wilson, M. R. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46, 3766-3774. Retrieved from http://www.sciencedirect.com/science/article/pii/S0263224113001061

Wilson, M., & Fisher, W. (2016). Preface: 2016 IMEKO TC1-TC7-TC13 Joint Symposium: Metrology across the Sciences: Wishful Thinking? Journal of Physics Conference Series, 772(1), 011001. Retrieved from http://iopscience.iop.org/article/10.1088/1742-6596/772/1/011001/pdf

Wilson, M., & Fisher, W. (2018). Preface of special issue, Metrology across the Sciences: Wishful Thinking? Measurement, 127, 577.

Wilson, M., & Fisher, W. (2019). Preface of special issue, Psychometric Metrology. Measurement, 145, 190.

 

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

April 13, 2019

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

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

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

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

A point of entry into thinking about how those conditions might be created is provided by a 2010 quote in the Miami Herald from Gus Speth, former Dean of the Yale School of Forestry and Environmental Studies (http://tinyurl.com/y7mqtzzn). Speth recounts his sense that scientific solutions to ecosystem and climate problems are insufficient because the actual causes of the problems are greed, selfishness, and apathy. So he appeals to religious leaders for help.

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

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

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

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

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

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

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

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

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

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

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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.

Taking the Scales of Justice Seriously as a Model for Sustainable Political Economies

February 28, 2019

We all take standards of measurement for granted as background assumptions that we never have to think about. But as technical, mundane, and boring as these standards are, they define our systems of fair dealing and just relations. The image of blind justice holding a balance scale is a universal ideal being compromised in multiple ways by chaotic forces in today’s complicated world arena.

Even so, astoundingly little effort is being invested in systematically exploring how the scales of justice might be more meaningfully and resiliently embedded within our social, economic, educational, health care, and political institutions. This well may be because the idea that people’s abilities, behaviors, and knowledge could be precisely weighed on a scale, like fruit in a grocery store, seems outrageously immoral, opening the door to treating people like commodities to be bought and sold. And even if the political will for such measures could be found, the regulatory enforcement of legally binding contracts and accounting standards appears so implausibly complicated as to make the whole matter not worth any serious consideration at all.

On the face of it, a literal application of the scales of justice to human affairs echoes ideas discredited so thoroughly and for so long that bringing them up in the here and now seems utterly ridiculous, at least, and perhaps truly dangerous, with no possible result except the crushing reduction of human beings to cogs in a soulless machine.

But what if there is some basic way in which measurement is misunderstood when it is taken to mean people will be treated like mass produced commodities for sale? What if we could measure, legally own, invest in, and profit from our literacy, health, and trustworthiness, in the same way we do with property and material things? What if precision measurement was not a tool for oppressive manipulation but a means of obtaining, sharing, and communicating valuable information? What if local contextual situations can be allowed a latitude of variation that does not negatively compromise navigable continuity?

Circumstances are conspiring to take humanity in new directions. Complex new necessities are nurturing the conception and birth of new innovations. A wealth of diverse possibilities for adaptive experimentation proposed in the past–sometimes the distant past–are finding new life in today’s technological context. And science has changed a lot in the last 100 years. In fact, the public is largely unaware that the old paradigm of mechanical reduction has been completely demolished and replaced with a new paradigm of organic emergence and complex adaptive systems. Even Newtonian mechanics and the basic number theory of arithmetic have had to be reworked. It is also true that very few experts have thought through what the demise of the mechanical root metaphor, and the birth of an organic ecosystem metaphor, means philosophically, socially, historically, and culturally.

Bottom-up manifestations of repeating patterns that can be scaled, measured, quantified, and explained open up a wide array of new opportunities for learning from shared experiences. And, just as humanity has long understood about music, we know now how to contextualize group and individual assessment and survey response patterns in ways that let everyone be what they are, uniquely improvising playful creative performances expressed using high tech instruments tuned to shared standards. A huge amount of conceptual and practical work needs to be done, but there are multiple historical precedents suggesting that betting against human ingenuity would be a losing wager.

Two new projects I’m involved in concerning sustainability impact investing and a metrology center for categorical measures begin a new exploration of the consequences of this paradigm shift for our image of the scales of justice as representing a moral imperative. These projects ask whether more complex combinations of mathematics, experiment, technology, and theory can be overtly conceived and implemented in terms of participatory and democratic social and cognitive ecosystems. If so, we may then find our way to new standards of measurement, new languages, and new forms of social organization sufficient to redefining what we take for granted as satisfying our shared sense of fair dealing and just relations.

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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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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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So you say knowledge wants to be free?

January 26, 2019

If knowledge wants to be free, why do we work so hard keeping it trapped in scores and ratings whose meanings change depending on which questions were asked and who answered them?

Why don’t we liberate knowledge from its many prisons by embodying it in measurement systems that mean the same thing (within the range of uncertainty) no matter which questions on a topic are asked and no matter who answers them?

We routinely share knowledge quickly and easily when it’s about time, length, temperature, energy, mass, etc. Methods, theories, models, and tools developed over the last 90+ years show how we could be doing the same thing for literacy, health, functionality, environmental management, and every other major area of concern in the UN Sustainability Development Goals.

There’s a lot of talk among sustainability advocates about how urgent the need is for transformative efforts, investments, and technologies. It seems to me that sense of urgency will never be more than empty talk as long as we go on willfully ignoring the fact that we hold the keys to the chains that bind us.

 

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New Ideas on How to Realize the Purpose of Capital

September 20, 2018

I’d like to offer the following in reply to James Militzer, at https://nextbillion.net/deciphering-emersons-tears-time-impact-investing-lower-expectations/.

Rapid advances toward impact investing’s highest goals of social transformation are underway in quiet technical work being done in places no one is looking. That work shares Jed Emerson’s sentiments expressed at the 2017 Social Capital Markets conference, as he is quoted in Militzer’s NextBillion.net posting, that “The purpose of capital is to advance a more progressively free and just experience of life for all.” And he is correct in what Militzer reported he said the year before, that we need a “real, profound critique of current practices within financial capitalism,” one that would “require real change in our own behavior aside from adding a few funds to our portfolios here or augmenting a reporting process there.”

But the efforts he and others are making toward fulfilling that purpose and articulating that critique are incomplete, insufficient, and inadequate. Why? How? Language is the crux of the matter, and the issues involved are complex and technical. The challenge, which may initially seem simplistic or naive, is how to bring human, social, and environmental values into words. Not just any words, but meaningful words in a common language. What is most challenging is that this language, like any everyday language, has to span the range from abstract theoretical ideals to concrete local improvisations.

That means it cannot be like our current languages for expressing human, social, and environmental value. If we are going to succeed in aligning those forms of value with financial value, we have a lot of work to do.

Though there is endless talk of metrics for managing sustainable impacts, and though the importance of these metrics for making sustainability manageable is also a topic of infinite discussion, almost no one takes the trouble to seek out and implement the state of the art in measurement science. This is a crucial way, perhaps the most essential way, in which we need to criticize current practices within financial capitalism and change our behaviors. Oddly, almost no one seems to have thought of that.

That is, one of the most universally unexamined assumptions of our culture is that numbers automatically stand for quantities. People who analyze numeric data are called quants, and all numeric data analysis is referred to as quantitative. That is the case, but almost none of these quants and quantitative methods involve actually defining, modeling, identifying, evaluating, or applying an substantive unit of something real in the world that can be meaningfully represented by numbers.

There is, of course, an extensive and longstanding literature on exactly this science of measurement. It has been a topic of research, philosophy, and practical applications for at least 90 years, going back to the work of Thurstone at the University of Chicago in the 1920s. That work continued at the University of Chicago with Rasch’s visit there in 1960, with Wright’s adoption and expansion of Rasch’s theory and methods, and with the further work done by Wright’s students and colleagues in the years since.

Most importantly, over the last ten years, metrologists, the physicists and engineers who maintain and improve the SI units, the metric system, have taken note of what’s been going on in research and practice involving the approaches to measurement developed by Rasch, Wright, and their students and colleagues (for just two of many articles in this area, see here and here). The most recent developments in this new metrology include

(a) initiatives at national metrology institutes globally (Sweden and the UK, Portugal, Ukraine, among others) to investigate potentials for a new class of unit standards;

(b) a special session on this topic at the International Measurement Confederation (IMEKO) World Congress in Belfast on 5 September 2018;

(c) the Journal of Physics Conference Series proceedings of the 2016 IMEKO Joint Symposium hosted by Mark Wilson and myself at UC Berkeley;

(d) the publication of a 2017 book on Ben Wright edited by Mark Wilson and myself in Springer’s Series on Measurement Science and Technology; and

(e) the forthcoming October 2018 special issue of Elsevier’s Measurement journal edited by Wilson and myself, and a second one currently in development.

There are profound differences between today’s assumptions about measurement and how a meaningful art and science of precision measurement proceeds. What passes for measurement in today’s sustainability economics and accounting are counts, percentages, and ratings. These merely numeric metrics do not stand for anything that adds up the way they do. In fact, it’s been repeatedly demonstrated over many years that these kinds of metrics measure in a unit that changes size depending on who or what is measured, who is measuring, and what tool is used to measure. What makes matters even worse is that the numbers are usually taken to be perfectly precise, as uncertainty ranges, error terms, and confidence intervals are only sporadically provided and are usually omitted.

Measurement is not primarily a matter of data analysis. Measurement requires calibrated instruments that can be read as standing for a given amount of something that stays the same, within the uncertainty range, no matter who is measuring, no matter what or who is measured, and no matter what tool is used. This is, of course, quite an accomplishment when it can be achieved, but it is not impossible and has been put to use in large scale practical ways for several decades (for instance, see here, here, and here). Universally accessible instruments calibrated to common unit standards are what make society in general, and markets in particular, efficient in the way of projecting distributed network effects, turning communities into massively parallel stochastic computers (as W. Brian Arthur put it on p. 6 of his 2014 book, Complexity Economics).

These are not unexamined assumptions or overly ideal theoretical demands. They are pragmatic ways of adapting to emergent patterns in various kinds of data that have repeatedly been showing themselves around the world for decades. Our task is to literally capitalize on these nonhuman forms of life by creating multilevel, complex ecosystems of relationships with them, letting them be what they are in ways that also let us represent ourselves to each other. (Emerson quotes Bruno Latour to this effect on page 136 in his new book, The Purpose of Capital; those familiar with my work will know I’ve been reading and citing Latour since the early 1980s).

So it seems to me that, however well-intentioned those promoting impact investing may be, there is little awareness of just how profound and sweeping the critique of current practices needs to be, or of just how much our own behaviors are going to have to change. There are, however, truly significant reasons to be optimistic and hopeful. The technical work being done in measurement and metrology points toward possibilities for extending everyday language into a pragmatic idealism that does not require caving in to either varying local circumstances or to authoritarian dictates.

The upside of the situation is that, as so often happens in the course of human history, this critique and the associated changes are likely to have that peculiar quality captured in the French expression, “plus ça change, plus c’est la même chose” (the more things change, the more they stay the same). The changes in process are transformative, but will also be recognizable repetitions of human scale patterns.

In sum, what we are doing is tuning the instruments of the human, social, and environmental sciences to better harmonize relationships. Just as jazz, folk, and world music show that creative improvisation is not constrained by–but is facilitated by–tuning standards and high tech solutions, so, too, can we make that the case in other areas.

For instance, in my presentation at the IMEKO World Congress in Belfast on 5 September, I showed that the integration of beauty and meaning we have within our grasp reiterates principles that date back to Plato. The aesthetics complement the mathematics, with variations on the same equations being traceable from the Pythagorean theorem to Newton’s laws to Rasch’s models for measurement (see, for instance, Fisher & Stenner, 2013). In many ways, the history of science and philosophy continues to be a footnote to Plato.

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

September 18, 2018

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

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

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

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

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

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A Yet Simpler Take on Making Sustainability Self-Sustaining

September 1, 2018

The point of focusing on sustainability is to balance human interests with a long term view of life on earth. Depleting resources as though they will be always available plainly is no way to plan for a safe and pleasant future. But it seems to me something is missing in the way we approach sustainability. Every time I see any efforts aimed at rebalancing resource usage with a long term view of the Earth’s capacity to support us, what do I see? I see solutions that cost a lot, and people saying that the costs are the price we have to pay for the mistakes that have been made, and for a viable future. And so I also see a lot of procrastination, delays, and reluctance to commit to sustainable policies and practices.

Why? Because, first, there are a great many people who cannot afford to live in the world as it is, right now, simply bearing their existing day-to-day costs. Even in the richest countries, huge proportions of people live hand to mouth, or very nearly so. Second, it’s hard to detect and punish freeloaders. Many people, companies, and governments are willing to hold off committing to sustainability in the hope that some technological fix will come along and spare them avoidable costs.

So, my question is, and I do not say this at all in jest or with any sense of irony or sarcasm: how do we make sustainability fun and profitable? How can we make sustainability economically self-sustaining? How can we make sustainability into a growth industry?

My answer to those questions is, by improving the quality of information on sustainability impacts. What does that mean? Why should that have anything to do with making sustainability fun and profitable? What improving the quality of information on sustainability impacts means is measuring it well, using methods and models that have been used in research and practice for more than 90 years. What we need is a Human, Social, and Natural Capital Metric System. or an International System of Units for Human, Social, and Natural Capital.

As we all know from the existing SI (metric system) units, high quality information makes it much easier to communicate value. Easier communication means lower transaction costs, and lower transaction costs mean that it becomes very inexpensive to find out how much of a sustainability impact is available, and what quality it is. High quality information enables grassroots bottom up efforts coordinating the decisions and behaviors of everyone everywhere. Managers would be able to dramatically improve quality in domains of human, social, and environmental value the way they do now for manufactured value. And investors would be able to reward innovation in those areas in ways they currently cannot.

For instance, with high quality sustainability impact measures, you’d be able to buy shares of stock in a new global carbon reduction effort that realistically projects it is on track to reverse climate change back its 1980 status. If someone came out with a better carbon reduction product that would make it possible to get the job done faster or at lower cost, we would have the information we need to quickly shift the flow of resources to the better product.

Speaking to other components of the UN’s Sustainability Development Goals, maybe people need to wonder why they cannot go buy 250 units of additional literacy right now? Why can’t you get a good price on a specific amount of literacy gain for your ten-year-old child from a few minutes of competitive shopping? And while you’re at it, maybe you could catch a special sale on 470 units of improved physical functionality for your great aunt who just had a hip replacement. Oh, she doesn’t need it because she’s got herself listed in a health capital investment bond likely to pay a 6% return? Well, maybe you should sink some funds into one of those contracts!

To take up the SDG 16.1 issue, if efforts to reduce armed violence were measured with the same level of information quality as kilowatt hours, that form of social capital product would be available in market transactions just the same way manufactured capital products like electricity are now. Conversely, your personal efforts at reducing armed violence, or improving someone’s literacy, or helping your great aunt with gains in physical functionality—all of these are investments of your skills and abilities that will pay back cash value to you. And because having fun with the kids, and getting out for recreational activities, are healthful things to do, enjoyment also should pay dividends.

Maybe this focus on fun and profit in making sustainability economically self-sustaining might finally find some traction for efforts in this area. Sustainability commerce could be a way of talking about these issues that will speak to matters more directly and practically. We’ll see how that works out as I try it on people in the near future.

 

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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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