Archive for the ‘sustainability’ Category

Measurement-Informed Logic Model for Sustainable Change In Empowering Participatory Social Ecologies

September 30, 2022

This is a first draft that hopefully will be picked up, modified, and widely circulated.

Footnotes
1.  See Fisher (2022a) and Knoster, et al. (2000).
2. The confusion of numeric counts for measured quantities is a debilitating error that stands as nothing short of a viral pandemic of miscommunication and short-circuited efforts intended to advance the greater good. Everyone knows full well that there is no way to tell who has more rock from counts of rocks, yet we persist in assuming counts of events, attendees, correct answers, etc. are adequate measurements. Such counts are not and never will be measurements. To stop confusing numeric trees for the quantitative forest we have to demand improved measurements. See references for explanations, alternatives, theory, and practice.
3. The ladder of stakeholder empowerment is widely used by governments around the world as a frame of reference defining a progression of levels ranging from being INFORMED to CONSULTED to INVOLVED to COLLABORATING to EMPOWERED. This ladder can be built into measurements in a way that lets ecosystem stakeholders and leaders know where they are relative to where they have been, their goals, what comes next, and their special strengths and weaknesses. See the references by Morrison and Fisher, Jami and Walsh, Jankowski, and Ortiz and Huber-Heim, listed below for more information.

References
Barney, M., & Fisher, W. P., Jr. (2016, April). Adaptive measurement and assessment. Annual Review of Organizational Psychology and Organizational Behavior, 3, 469-490. Retrieved from https://www.annualreviews.org/doi/abs/10.1146/annurev-orgpsych-041015-062329
Bateson, G. (1978, Spring). Number is different from quantity. CoEvolution Quarterly, 17, 44-46 [Reprinted from pp. 53-58 in Bateson, G. (1979). Mind and Nature: A Necessary Unity. New York: E. P. Dutton.]. Retrieved from http://www.wholeearth.com/issue/2017/article/295/number.is.different.from.quantity
Cano, S., Pendrill, L., Melin, J., & Fisher, W. P., Jr. (2019). Towards consensus measurement standards for patient-centered outcomes. Measurement, 141, 62-69. Retrieved from https://doi.org/10.1016/j.measurement.2019.03.056
Fisher, W. P., Jr. (2021). Bateson and Wright on number and quantity: How to not separate thinking from its relational context. Symmetry, 13(1415). Retrieved from https://doi.org/10.3390/sym13081415
Fisher, W. P., Jr. (2022a). Contrasting roles of measurement knowledge systems in confounding or creating sustainable change. Acta IMEKO, in press.
Fisher, W. P., Jr. (2022b). Measurement systems, brilliant results, and brilliant processes in healthcare: Untapped potentials of person-centered outcome metrology for cultivating trust. In W. P. Fisher, Jr. & S. Cano (Eds.), Person-centered outcome metrology: Principles and applications for high stakes decision making. Cham: Springer.
Fisher, W. P., Jr., & Stenner, A. J. (2018). Ecologizing vs modernizing in measurement and metrology. Journal of Physics Conference Series, 1044(012025), [http://iopscience.iop.org/article/10.1088/1742-6596/1044/1/012025].
Hopper, T. (2019). Stop accounting myopia:-think globally: A polemic. Journal of Accounting & Organizational Change, 15(1), 87-99.
Hutchins, E. (2014). The cultural ecosystem of human cognition. Philosophical Psychology, 27(1), 34-49.
Jami, A. A., & Walsh, P. R. (2017). From consultation to collaboration: A participatory framework for positive community engagement with wind energy projects in Ontario, Canada. Energy Research & Social Science, 27, 14-24.
Jankowski, P. (2009). Towards participatory geographic information systems for community-based environmental decision making. Journal of Environmental Management, 90(6), 1966-1971.
Knoster, T. P., Villa, R. A., & Thousand, J. S. (2000). A framework for thinking about systems change. In R. A. Villa & J. S. Thousand (Eds.), Restructuring for caring and effective education: Piecing the puzzle together, 2nd Ed. (pp. 93-128). Baltimore: Paul H. Brookes.
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
Mari, L., Wilson, M., & Maul, A. (2021). Measurement across the sciences. Cham: Springer.
Michell, J. (1986). Measurement scales and statistics: A clash of paradigms. Psychological Bulletin, 100, 398-407.
Morrison, J., & Fisher, W. P., Jr. (2018). Connecting learning opportunities in STEM education: Ecosystem collaborations across schools, museums, libraries, employers, and communities. Journal of Physics: Conference Series, 1065(022009). doi:10.1088/1742-6596/1065/2/022009
Morrison, J., & Fisher, W. P., Jr. (2019). Measuring for management in Science, Technology, Engineering, and Mathematics learning ecosystems. Journal of Physics: Conference Series, 1379(012042). doi:10.1088/1742-6596/1379/1/012042
Morrison, J., & Fisher, W. P., Jr. (2020, September 1). The Measure STEM Caliper Development Initiative [Online]. In http://bearcenter.berkeley.edu/seminar/measure-stem-caliper-development-initiative-online (Ed.), BEAR Seminar Series. BEAR Center, Graduate School of Education: University of California, Berkeley.
Morrison, J., & Fisher, W. P., Jr. (2021). Caliper: Measuring success in STEM learning ecosystems. Measurement: Sensors, 18, 100327. Retrieved from https://doi.org/10.1016/j.measen.2021.100327
Morrison, J., & Fisher, W. P., Jr. (2022). Caliper: Steps to an ecologized knowledge infrastructure for STEM learning ecosystems in Israel. Acta IMEKO, in press.
Ortiz, D., & Huber-Heim, K. (2017). From information to empowerment: Teaching sustainable business development by enabling an experiential and participatory problem-solving process in the classroom. The International Journal of Management Education, 15(2), 318-331.
Pendrill, L. R. (2019). Quality assured measurement: Unification across social and physical sciences. Cham: Springer.
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
Star, S. L., & Ruhleder, K. (1996). Steps toward an ecology of infrastructure: Design and access for large information spaces. Information Systems Research, 7(1), 111-134.
Sutton, J., Harris, C. B., Keil, P. G., & Barnier, A. J. (2010). The psychology of memory, extended cognition, and socially distributed remembering. Phenomenology and the Cognitive Sciences, 9(4), 521-560.
Creative Commons License

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.

Comments on VERRA Sustainable Development Verified Impact Standards

July 31, 2022

The landing page at https://verra.org states that:
“Verra catalyzes tangible climate action and sustainable development outcomes. Verra’s standards drive large-scale investment towards high-impact activities that tackle some of the most pressing environmental and social issues of our day.”

Verra’s six listed standards and programs includes one entitled, “Sustainable Development Verified Impact Standards.” Two documents providing details on this kind of standard are available for download. One concerns “Methodology for Coastal Resilience Benefits from Restoration and Protection of Tidal Wetlands.” The methodology lays out a descriptive group-level statistical model of an ordinal unit, and not a prescriptive individual-level measurement model of an interval unit. Even though the stem ‘measur-‘ at the root of ‘measured,’ ‘measurement,’ etc. appears 119 times in the standard’s 51 pages, there is no definition of a composite Coastal Resilience Benefits interval unit quantity and associated uncertainty, nor is there any mention of experimental tests of the hypothesis that such a unit quantity can be identified and estimated.

The standard takes it for granted that physical measurements of distance, mass, volume, time, temperature, etc. are sufficient to the task of measuring coastal resilience benefits. But this is what is termed in logic as a category mistake, an ecological fallacy, or what Alfred North Whitehead (1925, pp. 52-58) called the “fallacy of misplaced concreteness.” Gregory Bateson (1972, pp. 73, 180-185, 491-495) similarly made much of the epistemological errors committed when the map is confused for the territory, the forest for the trees. In short, measuring coastal resilience benefits demands that this construct (also known in metrological terms as a measurand) itself be modeled, estimated, and calibrated in an identified and defined interval unit quantity.

Extensive and longstanding authoritative resources on measurement models supporting metrologically quality-assured instrument calibration traceability of this kind are available (Luce & Tukey, 1964; Rasch, 1960, 1961; Wright, 1977, 1997; Bond & Fox, 2015; Fisher & Wilson, 2015; Fisher & Wright, 1994; Mari & Wilson, 2014; Mari, et al., 2021; Pendrill, 2019; Pendrill & Fisher, 2015; Wilson, 2005, 2013a/b; Wilson & Fisher, 2016, 2019; etc.), with a similarly voluminous array of sustainable development applications (Cano, et al., 2019; Fisher, 2020a/b, 2021a/b; Fisher, et al., 2019, 2021; Fisher & Wilson, 2019; Madhala & Fisher, 2022; Moral, et al., 2006, 2014, 2016; Kaiser & Wilson, 2000, 2004; etc.). Writing in 1986, Narens and Luce (1986, pp. 167-169) pointed out that additive conjoint log-interval models developed in the 1960s (Luce & Tukey, 1964; Rasch, 1960, 1961; Wright, 1997) were “widely accepted” as providing access to fundamental measurement. Unfortunately, we have yet to even begin capitalizing on the opportunities for scientific, economic, social, and environmental progress offered by these models (Fisher, 2011, 2012a/b, 2020a).

Where statistical models are concerned with group-level processes occurring in the relations between variables, measurement models focus on substantive processes as they impact individuals. Actionable, meaningful management gets a grip on things in the world only in terms of measurements that give insight into what can be done in specific instances, and that can then be communicated in a common language across those instances. Statistical models have a number of debilitating shortcomings that make them highly unsatisfactory as a basis for quantification (Fisher, 2022). In addition to not positing and testing for interval quantities, these models do not:

  • articulate the individual-level response process;
  • map the development continuum;
  • provide individual level quantity, uncertainty, or consistency estimates;
  • meaningfully reduce data volume by an order of magnitude;
  • support the development of a metrologically quality assured instrument calibration network;
  • report out individual and group measurements in a way showing what has been accomplished relative to overall goals, what comes next, and special strengths and weaknesses;
  • enable the cost accounting, arbitrage, and pricing of unit outcomes;
  • nonreductively quantify living processes in ways that make them objectively reproducible over time and space;
  • represent individual- and group-level properties in comparable terms that support legal title to personal stocks of human, social, and natural capital, and profitable investments in and returns from those stocks.

For instance, Sections 9.1 and 9.2 in the coastal wetlands standard lists all the parameters to be monitored. Two comments pertain. First, these “parameters” are actually indicators that ought to be combined into an overarching composite model testing the statistical sufficiency of the observations–i.e., their capacity to serve as a basis for estimating interval unit quantities and uncertainties. In measurement theory and practice, the model parameters are the mathematical terms in the equation specifying the stimulus and response variables being quantified. Estimates signify the value obtained as a result of the combined inputs of all the indicators, no matter which particular subset of them is administered, and no matter which particular sample is measured.

The second point concerns the content of the indicators, which have been chosen because they are fairly easily measured in the physical values of distance, mass, volume, time, temperature, etc. A composite model and metrological unit system should also include a more actionable and meaningful definition of the measurand, one articulated as a developmental progression defined along a continuum ranging from most easily implemented to least easily implemented. This kind of integrated psychophysics is eminently suited to taking advantage of advanced measurement modeling (Camargo & Henson, 2013, 2015; Fisher, Melin, & Möller, 2021; Massof & McDonnell, 2012; Pendrill & Fisher, 2015; Powers & Fisher, 2018, 2022).

The practical application of the metrics and their comparability depends on obtaining usefully precise (a) theoretical predictions of indicator and project locations on the instrument (a construct map); (b) repeated demonstrations of reproducible and empirically stable data-based indicator and project location estimates (Wright maps); and (c) end user reports displaying indicator response values ordered along the mapped variable showing what has been accomplished, where the project stands in relation to its goals, what comes next in advancing its program, and where its actionable strengths and weaknesses lie.

Clear and significant progress in addressing the urgent needs for solutions to today’s pressing challenges cannot reasonably be expected until advanced measurement modeling in support of quality-assured metrological traceability is explicitly included in the design and implementation of Verra’s and others’ sustainable development standards. Hopefully the day will soon arrive when that will be the case.

References

Bateson, G. (1972). Steps to an ecology of mind: Collected essays in anthropology, psychiatry, evoltion, and epistemology. Chicago: University of Chicago Press.

Bond, T., & Fox, C. (2015). Applying the Rasch model: Fundamental measurement in the human sciences, 3d edition. New York: Routledge.

Camargo, F. R., & Henson, B. (2013). Aligning physical elements with persons’ attitude: An approach using Rasch measurement theory. Journal of Physics Conference Series, 459(1), http://iopscience.iop.org/1742-6596/459/1/012009/pdf/1742-6596_459_1_012009.pdf.

Camargo, F. R., & Henson, B. (2015). Conceptualising computerized adaptive testing for measurement of latent variables associated with physical objects. Journal of Physics Conference Series, 588(1), 012012. doi:10.1088/1742-6596/588/1/012012

Cano, S., Pendrill, L., Melin, J., & Fisher, W. P., Jr. (2019). Towards consensus measurement standards for patient-centered outcomes. Measurement, 141, 62-69. Retrieved from https://doi.org/10.1016/j.measurement.2019.03.056

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

Fisher, W. P., Jr. (2012b, June 1). 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. (2020a). Contextualizing sustainable development metric standards: Imagining new entrepreneurial possibilities. Sustainability, 12(9661), 1-22. Retrieved from https://doi.org/10.3390/su12229661

Fisher, W. P., Jr. (2020b). Measuring genuine progress: An example from the UN Millennium Development Goals project. Journal of Applied Measurement, 21(1), 110-133

Fisher, W. P., Jr. (2021a). Bateson and Wright on number and quantity: How to not separate thinking from its relational context. Symmetry, 13(1415). Retrieved from https://doi.org/10.3390/sym13081415

Fisher, W. P., Jr. (2021b). Separation theorems in econometrics and psychometrics: Rasch, Frisch, two Fishers, and implications for measurement. Journal of Interdisciplinary Economics, OnlineFirst, 1-32. Retrieved from https://journals.sagepub.com/doi/10.1177/02601079211033475

Fisher, W. P., Jr. (2022). Contrasting roles of measurement knowledge systems in confounding or creating sustainable change. Acta IMEKO, in press.

Fisher, W. P., Jr., Melin, J., & Möller, C. (2021). Metrology for climate-neutral cities (RISE Research Institutes of Sweden AB No. RISE Report 2021:84). Gothenburg, Sweden:. RISE. Retrieved from http://ri.diva-portal.org/smash/record.jsf?pid=diva2%3A1616048&dswid=-7140

Fisher, W. P., Jr., Pendrill, L., Lips da Cruz, A., & Felin, A. (2019). Why metrology? Fair dealing and efficient markets for the United Nations’ Sustainable Development Goals. Journal of Physics: Conference Series, 1379(012023 [http://iopscience.iop.org/article/10.1088/1742-6596/1379/1/012023]). doi:10.1088/1742-6596/1379/1/012023

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. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2688260

Fisher, W. P., Jr., & Wilson, M. (2019). The BEAR Assessment System Software as a platform for developing and applying UN SDG metrics. Journal of Physics Conference Series, 1379(012041). Retrieved from https://doi.org/10.1088/1742-6596/1379/1/012041

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

Kaiser, F. G., & Wilson, M. (2000). Assessing people’s general ecological behavior: A cross-cultural measure. Journal of Applied Social Psychology, 30(5), 952-978.

Kaiser, F. G., & Wilson, M. (2004). Goal-directed conservation behavior: The specific composition of a general performance. Personality and Individual Differences, 36(7), 1531-1544. Retrieved from https://doi.org/10.1016/j.paid.2003.06.003

Luce, R. D., & Tukey, J. W. (1964). Simultaneous conjoint measurement: A new kind of fundamental measurement. Journal of Mathematical Psychology, 1(1), 1-27.

Madhala, T., & Fisher, W. P., Jr. (2022). Clothing, textile, and fashion industry sustainable impact measurement and management. Acta IMEKO, in press.

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

Mari, L., Wilson, M., & Maul, A. (2021). Measurement across the sciences (R. Morawski, G. Rossi, & others, Eds.). Springer Series in Measurement Science and Technology. Cham: Springer.

Massof, R. W., & McDonnell, P. J. (2012, April). Latent dry eye disease state variable. Investigative Ophthalmology & Visual Science, 53(4), 1905-1916. Retrieved from https://iovs.arvojournals.org/article.aspx?articleid=2188166

Moral, F. J., Álvarez, P., & Canito, J. L. (2006). Mapping and hazard assessment of atmospheric pollution in a medium sized urban area using the Rasch model and geostatistics techniques. Atmospheric Environment, 40(8), 1408-1418.

Moral, F. J., Rebollo, F. J., & Méndez, F. (2014). Using an objective model to estimate overall ozone levels at different urban locations. Stochastic Environmental Research and Risk Assessment, 28(3), 455-465.

Moral, F. J., Rebollo, F. J., Paniagua, L. L., García, A., & de Salazar, E. M. (2016). Application of climatic indices to analyse viticultural suitability in Extremadura, south-western Spain. Theoretical and Applied Climatology, 123(1-2), 277-289.

Narens, L., & Luce, R. D. (1986). Measurement: The theory of numerical assignments. Psychological Bulletin, 99(2), 166-180.

Pendrill, L. R. (2019). Quality assured measurement: Unification across social and physical sciences. Cham: Springer.

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

Powers, M., & Fisher, W. P., Jr. (2018). Toward a standard for measuring functional binocular vision: Modeling visual symptoms and visual skills. Journal of Physics Conference Series, 1065(132009). doi:10.1088/1742-6596/1065/13/132009

Powers, M., & Fisher, W. P., Jr. (2021). Physical and psychological measures quantifying functional binocular vision. Measurement: Sensors, 18, 100320. Retrieved from https://doi.org/10.1016/j.measen.2021.100320

Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests (Reprint, with Foreword and Afterword by B. D. Wright, Chicago: University of Chicago Press, 1980). Copenhagen, Denmark: Danmarks Paedogogiske Institut.

Rasch, G. (1961). On general laws and the meaning of measurement in psychology. In J. Neyman (Ed.), Proceedings of the fourth Berkeley symposium on mathematical statistics and probability: Volume IV: Contributions to biology and problems of medicine (pp. 321-333 [http://www.rasch.org/memo1960.pdf]). Berkeley, California: University of California Press.

Whitehead, A. N. (1925). Science and the modern world. New York: Macmillan.

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

Wilson, M. R. (2013a, April). Seeking a balance between the statistical and scientific elements in psychometrics. Psychometrika, 78(2), 211-236.

Wilson, M. R. (2013b). 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. P., Jr. (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. P., Jr. (2019). Preface of special issue, Psychometric Metrology. Measurement, 145, 190. Retrieved from https://www.sciencedirect.com/journal/measurement/special-issue/10C49L3R8GT

Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14(2), 97-116 [http://www.rasch.org/memo42.htm].

Wright, B. D. (1997). A history of social science measurement. Educational Measurement: Issues and Practice, 16(4), 33-45, 52 [http://www.rasch.org/memo62.htm]. Retrieved from https://doi.org/10.1111/j.1745-3992.1997.tb00606.x

Measurement Choices in Sustainable Development

June 28, 2020

Dividing Us, or Unifying Us?

Showing the Way, or Leading Astray?

Sustainable development measurement choices have significant effects on our capacities to coordinate and manage our efforts. The usual approach to sustainability metrics requires that all parties comparing impacts use the same indicators. Communities or organizations using different metrics are not comparable. Applications of the metrics to judge progress or to evaluate the effects of different programs focus on comparing results from individual indicators. The indicators with the biggest differences are the areas in which accomplishments are rewarded, or failings provoke rethinking.

A number of scientific and logical problems can be identified in this procedure, and these will be taken up in due course. At the moment, however, let us only note that advanced scientific modeling approaches to measuring sustainable development do not require all parties to employ the same indicators, since different sets of indicators can be made comparable via instrument equating and item banking methods. And instead of focusing on differences across indicators, these alternative approaches use the indicators to map the developmental sequence. These maps enable end users to locate and orient themselves relative to where they have been, where they want to go, and where to go next on their sustainability journey.

Separating sustainable development efforts into incommensurable domains becomes a thing of the past when advanced scientific modeling approaches are used. At the same time, these modeling approaches also plot navigable maps of the sustainability terrain.

Scientific modeling of sustainability measures offer other advantages, as well.

  • First, scientific measures always contextualize reported quantities with a standard error term, whereas typical metrics are reported as though they are perfectly precise, with no uncertainty.
  • Second, scientific measures are calibrated as interval measures on the basis of predictive theory and experimental evidence, whereas sustainability metrics are typically ordinal counts of events (persons served, etc.), percentages, or ratings.
  • Third, scientific measures summarize multiple indicators in a single quantity and uncertainty term, with no loss of information, whereas sustainability metrics are often reported as large volumes of numbers.

The advantages of investing in a scientific measurement modeling approach follow from its combination of general comparability across data sets, the mapping of the thing measured, the reporting of uncertainty terms, the interval quantity, and the removal of the information overload.

For more information, see other entries in this blog and:

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

Fisher, W. P., Jr. (2012, June 1). 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. (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. (2013). Imagining education tailored to assessment as, for, and of learning: Theory, standards, and quality improvement. Assessment and Learning, 2, 6-22.

Fisher, W. P., Jr. (2020). Measurements toward a future SI: On the longstanding existence of metrology-ready precision quantities in psychology and the social sciences. In G. Gerlach & K.-D. Sommer (Eds.), SMSI 2020 Proceedings (pp. 38-39). Wunstorf, Germany: AMA Service GmbH. Retrieved from https://www.smsi-conference.com/assets/Uploads/e-Booklet-SMSI-2020-Proceedings.pdf

Fisher, W. P., Jr. (2020). Measuring genuine progress: An example from the UN Millennium Development Goals project. Journal of Applied Measurement, 21(1), 110-133

Fisher, W. P., Jr., Pendrill, L., Lips da Cruz, A., Felin, A., &. (2019). Why metrology? Fair dealing and efficient markets for the United Nations’ Sustainable Development Goals. Journal of Physics: Conference Series, 1379(012023). doi:10.1088/1742-6596/1379/1/012023

Fisher, W. P., Jr., & Stenner, A. J. (2016). Theory-based metrological traceability in education: A reading measurement network. Measurement, 92, 489-496. Retrieved from http://www.sciencedirect.com/science/article/pii/S0263224116303281

Fisher, W. P., Jr., & Stenner, A. J. (2017, September 18). Towards an alignment of engineering and psychometric approaches to uncertainty in measurement: Consequences for the future. 18th International Congress of Metrology, 12004, 1-9. Retrieved from https://doi.org/10.1051/metrology/201712004

Fisher, W. P., Jr., & Stenner, A. J. (2018). Ecologizing vs modernizing in measurement and metrology. Journal of Physics Conference Series, 1044(012025), [http://iopscience.iop.org/article/10.1088/1742-6596/1044/1/012025].

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. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2688260

Fisher, W. P., Jr., & Wilson, M. (2020). An online platform for sociocognitive metrology: The BEAR Assessment System Software. Measurement Science and Technology, 31(034006). Retrieved from https://iopscience.iop.org/article/10.1088/1361-6501/ab5397/meta

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

Lips da Cruz, A., Fisher, W. P. J., Felin, A., & Pendrill, L. (2019). Accelerating the realization of the United Nations Sustainability Development Goals through metrological multi-stakeholder interoperability. Journal of Physics: Conference Series, 1379(012046).

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

Mari, L., & Wilson, M. (2020). Measurement across the sciences [in press]. Cham: Springer.

Pendrill, L. (2019). Quality assured measurement: Unification across social and physical sciences. Cham: Springer

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., & 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. (2019). Preface of special issue, Psychometric Metrology. Measurement, 145, 190. Retrieved from https://www.sciencedirect.com/journal/measurement/special-issue/10C49L3R8GT

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

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.

 

Creative Commons License
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.

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.

References

Akera, A. (2007). Constructing a representation for an ecology of knowledge. Social Studies of Science, 37(3), 413-441.

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

Blok, A., Nakazora, M., & Winthereik, B. R. (2016). Infrastructuring environments. Science as Culture, 25(1), 1-22.

Bowker, G. C. (2016). How knowledge infrastructures learn. In P. Harvey, C. B. Jensen & A. Morita (Eds.), Infrastructures and social complexity: A companion (pp. 391-403). New York: Routledge.

Bowker, G., Timmermans, S., Clarke, A. E., & Balka, E. (Eds). (2015). Boundary objects and beyond: Working with Leigh Star. Cambridge, MA: MIT Press.

Brain, R. (1998). Standards and semiotics. In T. Lenoir (Ed.), Inscribing science: Scientific texts and the materiality of communication (pp. 249-w84). Stanford, California: Stanford University Press.

Cano, S. J., & Hobart, J. C. (2011). The problem with health measurement. Patient Preference and Adherence, 5, 279-290.

Cano, S., Klassen, A. F., & Pusic, A. L. (2009). The science behind quality-of-life measurement: A primer for plastic surgeons. Plastic and Reconstructive Surgery, 123(3), 98e-106e.

Cano, S., Melin, J., Fisher, W. P., Jr., Stenner, A. J., Pendrill, L., & EMPIR NeuroMet 15HLT04 Consortium. (2018). Patient-centred cognition metrology. Journal of Physics: Conference Series, 1065, 072033.

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.

Cano, S., Pendrill, L., Melin, J., & Fisher, W. P., Jr. (2019). Towards consensus measurement standards for patient-centered outcomes. Measurement, in press.

Dawson, T. L. (2002, Summer). A comparison of three developmental stage scoring systems. Journal of Applied Measurement, 3(2), 146-89.

Dawson, T. L. (2002, March). New tools, new insights: Kohlberg’s moral reasoning stages revisited. International Journal of Behavioral Development, 26(2), 154-66.

Dawson, T. L. (2004, April). Assessing intellectual development: Three approaches, one sequence. Journal of Adult Development, 11(2), 71-85.

Dawson, T. L., & Stein, Z. (2011). We are all learning here: Cycles of research and application in adult development. In C. Hoare (Ed.), The Oxford handbook of reciprocal adult development and learning, 2nd Ed. (pp. 447-460). Oxford, England: Oxford University Press.

Fisher, W. P., Jr. (2009, November). Invariance and traceability for measures of human, social, and natural capital: Theory and application. Measurement: Concerning Foundational Concepts of Measurement Special Issue Section, 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, November 22). The birds and the bees of living meaning. LivingCapitalMetrics blog. https://livingcapitalmetrics.wordpress.com/2010/11/22/the-birds-and-the-bees-of-living-meaning/.

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. (2011). Metaphor as measurement, and vice versa: Convergence and separation of figure and meaning in a Mawri proverb [Modified version of a paper presented to the African Studies Association, 1996]. Social Science Research Network. http://ssrn.com/abstract=1747967

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, June 1). 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. (2013). Imagining education tailored to assessment as, for, and of learning: Theory, standards, and quality improvement. Assessment and Learning, 2, 6-22.

Fisher, W. P., Jr. (2014). The central theoretical problem of the social sciences. Rasch Measurement Transactions, 28(2), 1464-1466. http://www.rasch.org/rmt/rmt282.pdf

Fisher, W. P., Jr. (2017, September). Metrology, psychometrics, and new horizons for innovation. 18th International Congress of Metrology, Paris, 09007 [https://cfmetrologie.edpsciences.org/articles/metrology/pdf/2017/01/metrology_metr2017_09007.pdf].

Fisher, W. P., Jr. (2017). A practical approach to modeling complex adaptive flows in psychology and social science. Procedia Computer Science, 114, 165-174. https://doi.org/10.1016/j.procs.2017.09.027

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

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

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

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

Fisher, W. P., Jr., Oon, E. P.-T., & Benson, S. (2018). Applying Design Thinking to systemic problems in educational assessment information management. Journal of Physics Conference Series, 1044, 012012 [http://iopscience.iop.org/article/10.1088/1742-6596/1044/1/012012].

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

Fisher, W. P., Jr., & Stenner, A. J. (2011, January 1). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36

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

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., & Stenner, A. J. (2018). Ecologizing vs modernizing in measurement and metrology. Journal of Physics Conference Series, 1044, 012025.

Fisher, W. P., Jr., & Stenner, A. J. (2017, September 18). Towards an alignment of engineering and psychometric approaches to uncertainty in measurement: Consequences for the future. 18th International Congress of Metrology, 12004, 1-9. https://doi.org/10.1051/metrology/201712004

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

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

Hutchins, E. (2014). The cultural ecosystem of human cognition. Philosophical Psychology, 27(1), 34-49.

Jasanoff, S. (2005). Designs on nature: Science and democracy in Europe and the United States. Princeton, NJ: Princeton University Press.

Jasanoff, S. (2015). Future imperfect: Science, technology, and the imaginations of modernity. In S. Jasanoff & S.-H. Kim (Eds.), Dreamscapes of modernity: Sociotechnical imaginaries and the fabrication of power (pp. 1-22). Chicago: University of Chicago Press.

Jasanoff, S., & Martello, M. L. (Eds.) (2004). Earthly politics: Local and global in environmental governance. (Politics, Science, and the Environment). Cambridge, MA: MIT Press.

Kjellberg, H., & Helgesson, C.-F. (2006). Multiple versions of markets: Multiplicity and performativity in marketing practice. Industrial Marketing Management, 35, 839-855.

Lampland, M., & Star, S. L. (Eds.). (2008). Standards and their stories: How quantifying, classifying, and formalizing practices shape everyday life. Ithaca, NY: Cornell University Press.

Latour, B. (1990). Postmodern? No, simply amodern: Steps towards an anthropology of science. Studies in History and Philosophy of Science, 21(1), 145-171.

Latour, B. (1991). The impact of science studies on political philosophy. Science, Technology, & Human Values, 16(1), 3-19.

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

Latour, B. (1998). To modernise or ecologise? That is the question. In B. Braun & N. Castree (Eds.), Remaking reality: Nature at the millennium (pp. 221-242). London: Routledge.

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

Latour, B. (2009). On the modern cult of the factish gods (H. MacLean & C. Porter, Trans.). Durham, NC: Duke University Press.

Latour, B. (2010). Tarde’s idea of quantification. In M. Candea (Ed.), The social after Gabriel Tarde: Debates and assessments (pp. 145-162). London: Routledge.

Latour, B. (2011). Love your monsters: Why we must care for our technologies as we do our children. Breakthrough Journal, 2, 21-28. http://thebreakthrough.org/index.php/journal/past-issues/issue-2/love-your-monsters

Latour, B. (2014, February 26). On some of the affects of capitalism. Lecture given at the Royal Academy, Copenhagen, Denmark. Retrieved from http://www.bruno-latour.fr/sites/default/files/136-AFFECTS-OF-K-COPENHAGUE.pdf.

Latour, B., & Callon, M. (2011). “Thou shall not calculate!” or how to symmetricalize gift and capital. Revista De Pensamiento e Investifation Social, 11(1), 171-192.

Latour, B., & Lépinay, V. A. (2010). The science of passionate interests: An introduction to Gabriel Tarde’s economic anthropology. Chicago: Prickly Paradigm Press.

Lenoir, T. (Ed.). (1997). Instituting science: The cultural production of scientific disciplines (T. Lenoir & H. U. Gumbrecht, Eds.). Writing Science. Stanford, CA: Stanford University Press.

Lenoir, T. (1998). Inscribing science: Scientific texts and the materiality of communication. Stanford, California: Stanford University Press.

Li, E. Y., Commons, M. L., Miller, J. G., Robbinet, T. L., Marchand, H., Ost, C. M. et al. (2014, September). Relationship among measures within the social and moral development domain. Behavioral Development Bulletin, 19(3), 106-113.

Nersessian, N. J. (2012). Engineering concepts: The interplay between concept formation and modeling practices in bioengineering sciences. Mind, Culture, and Activity, 19, 222-239.

Nersessian, N. J. (2015). Conceptual innovation on the frontiers of science. In E. Margolis & S. Laurence (Eds.), The conceptual mind: New directions in the study of concepts (pp. 455-474). Cambridge, MA: MIT Press.

Nespor, J. (2011). Devices and educational change. Educational Philosophy and Theory, 43(S1).

Overton, W. F. (2015). Processes, relations and Relational-Developmental-Systems. In W. F. Overton & P. C. M. Molenaar (Eds.), Theory and Method. Volume 1 of the Handbook of child psychology and developmental science (7th Ed.) (pp. 9-62). Hoboken, NJ: Wiley.

Schaffer, S. (1992). Late Victorian metrology and its instrumentation: A manufactory of Ohms. In R. Bud & S. E. Cozzens (Eds.), Invisible connections: Instruments, institutions, and science (pp. 23-56). Bellingham, WA: SPIE Optical Engineering Press.

Schaffer, S. (1997). Metrology, metrication, and Victorian values. In B. Lightman (Ed.), Victorian science in context (pp. 438-474). Chicago: University of Chicago Press.

Shapin, S. (1994). A social history of truth: Civility and science in seventeenth-century England. Chicago, Illinois: University of Chicago Press.

Shapin, S., & Schaffer, S. (1985). Leviathan and the air-pump: Hobbes, Boyle, and the experimental life. Princeton, NJ: Princeton University Press.

 

Creative Commons License
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 (Alder, 2002). The image of blind justice holding a balance scale is a universal ideal that is 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? Of cultivating trust? 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 (Fisher, 2012, 2021, 2023a/b). 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, mean philosophically, socially, historically, and culturally.

Bottom-up manifestations of repeating patterns–that can be scaled, measured, quantified, explained, and qualified in individually customized feedback–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.

New projects I’m involved in concerning sustainability and metrology 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.

Reference

Alder, K. (2002). The measure of all things. The Free Press.

Fisher, W. P., Jr. (2012, May/June). What the world needs now: A bold plan for new standards [Third

place, 2011 NIST/SES World Standards Day paper competition]. Standards Engineering, 64(3), 1

& 3-5 [http://ssrn.com/abstract=2083975].

Fisher, W. P., Jr. (2021). Bateson and Wright on number and quantity: How to not separate thinking

from its relational context. Symmetry, 13(1415). https://doi.org/10.3390/sym13081415

Fisher, W. P., Jr. (2023a). Foreword: Koans, semiotics, and metrology in Stenner’s approach to

measurement-informed science and commerce. In W. P. Fisher, Jr. & P. J. Massengill (Eds.),

Explanatory models, unit standards, and personalized learning in educational measurement:

Selected papers by A. Jackson Stenner (pp. ix-lxx). Springer Open Access. https://link.springer.com/book/10.1007/978-981-19-3747-7

Fisher, W. P., Jr. (2023b). Measurement systems, brilliant results, and brilliant processes in healthcare:

Untapped potentials of person-centered outcome metrology for cultivating trust. In W. P. Fisher,

Jr. & S. Cano (Eds.), Person-centered outcome metrology: Principles and applications for high

stakes decision making (pp. 357-396). Springer Open Access. https://link.springer.com/book/10.1007/978-3-

031-07465-3

Creative Commons License
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.

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.

Creative Commons License
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.

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.

 

Creative Commons License
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.

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….

 

Creative Commons License
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.

 

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.

Creative Commons License
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.