Archive for the ‘measurement’ Category

Transformative love!

June 4, 2019

Transformative love! How about a pragmatically effective sense of loving transformation?

  • How about if we lovingly care for our social impact measurement technologies like we do our children (to adapt Bruno Latour’s suggestion)?
  • How about if we lovingly care enough to choose discourse over violence and we quit committing the violence of the premature conclusions we draw from insufficient social impact information (echoing Paul Ricoeur)?
  • How about if we do more to lovingly care for the unity and sameness of the objects of our sustainable impact conversations (taking up Hans-Georg Gadamer’s terms)?
  • How about if we lovingly care enough to prioritize feminist diffractions over masculine tests of strength (following Donna Haraway)?
  • What if we lovingly cared enough for social innovation to model it on the fecund relationships that conceive, gestate, midwife, and nurture new life to maturity (channeling Luce Irigaray)?
  • What if we lovingly care about keeping thinking connected with the ecosystem context of relationships enough to create a new social innovation information infrastructure (tapping the words of Susan Leigh Star)?

Here at the Social Innovation Summit, Valerie Kaur’s call to revolutionary love, leading with love, does a fantastic job of spelling out the power of the birthing and midwifery metaphor. When people like her make the connection, there’s no limit to where humanity will go.

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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.

References

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

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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

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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.

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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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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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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.

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].

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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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Remembering Elie Wiesel’s teaching

November 21, 2018

Paraphrasing the last paragraph from a recent USA Today story on a new book about Elie Wiesel (linked in below):

“Language does more than just provide a means of sharing ideas and memories. Language embodies the human desire for meaning, for the infinite, for surpassing limits, for community and the communication of transcendent experiences of beauty.”

But language cuts two ways. It provides a medium for transcending limits while it nonetheless has its own limits. Wiesel says language can be corrupted and contaminated by human cruelty. I think this allows human will more latitude and agency than it actually has. I think broad scale corruption and cruelty are artifacts or by-products of the limits of language.

Corruption and cruelty scale up when human experience encounters new challenges for which the available language is inadequate and new conceptual frameworks are slow to emerge. Dark fears and destructive hate go on a rampage when ignorance rules and understanding is scarce. Seeing these times in human history as products of individual will is a point of view that is itself situated within the overly narrow limits of a language that has long outlived its usefulness.

Our challenge is how to find our way to new languages better able to inspire confident cooperation and communication across our diverse differences. On the face of it, this may seem to be an insurmountable barrier demanding we look elsewhere for creative opportunities. I beg to differ.

Root metaphors captivate the imaginations of millions, as with the ‘Love is a rose’ metaphor of romance, the Christian ‘God is Love’ metaphor, or the ‘clockwork universe’ metaphor of Newtonian physics. But in today’s age of global humanity, a new poetics capable of making general sense of individual experience seems perpetually out of reach.

The complexity of the problem is truly staggering. In fact, the way we define the problem is the crux of the matter. As I’ve tried to explain before, the problem is the problem.

That is, today we face a meta-problem asking, what is the metaphor for metaphor? How do we transform implicit background assumptions about the limits of language into explicit objects of operations on language? How do we attain that complex level of understanding where we do not look upon corruption and cruelty simply as matters of individual human will but as the logical consequence of our failure to create institutions modeled on language’s complex combination of navigable continuity and local improvisation?

Can we go beyond the often impossibly out of reach but still inadequate compassion for those who commit atrocities, who are twisted into grotesque forms by hate? Can we actually come to understand the multilevel complexity, limits, and processes of language and metaphor well enough to intentionally cultivate new organic social and cognitive ecosystems? Can we see language as a collectively projected knowledge technology? Can we learn how to foster meaningful conceptual determinations embodied in words that stand for real things in the world? Can we apply language itself as a model for transforming our educational, health care, market, social service, and government institutions?

I say not only that yes, we can; I say yes, we have. This new level of complexity in approaching language has been taking shape for decades, and in some respects for centuries. It is emerging now on multiple fronts across a wide range of fields. This is the focus of my recent work on the multilevel complexity of sociocognitive ecosystems, and on the developmental, horizontal, and vertical coherence of integrated assessment and instruction. It’s a huge challenge, but having seen clearly that the biggest problem is how we define the problem, I am cautiously optimistic humanity will find a way.

Meyer, Zlati. 2018. New book shares Elie Wiesel’s powerful classroom lessons from the Holocaust. USA Today, 14 November.

Print version appeared in Life section, pp. 1D, 6D. Tuesday, 20 November, titled Elie Wiesel’s classroom lessons resonate.

https://www.usatoday.com/story/life/books/2018/11/14/elie-wiesels-classroom-lessons-holocaust-book-witness-ariel-burger-book-review/1897795002/

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On the recent Pew poll contrasting differences as to the “very big” problems we face today

October 20, 2018

An online news item appearing on 15 October 2018 proclaims that “Americans don’t just disagree on the issues. They disagree on what the issues are.” The article, by Dylan Scott on the Vox website, reports on a poll conducted by the Pew Research Center, involving registered voters in the U.S., between 24 September and 7 October. Polarizing disagreement is a recurring theme in the world, and keeping the tension up sells ads, so it is not surprising to see the emphasis in both the article and in the Pew report on major differences in people’s perceptions of what counts as a “very big” problem in the U.S. today. But a closer look at the data gives hope for finding ways to communicate across barriers that may look more significant than they actually are.

There’s no mention in the article of the sampling error, uncertainty, or confidence level, but the Pew site indicates that, overall, sampling error is 1.5%. But the Vox article mentions only the total sample size and fails to say that the registered voter portion of the respondents is smaller by a couple of thousand. Further, the sampling error jumps up to 2.6% for respondents indicating support for a Republican candidate, and to 2.3% for respondents supporting a Democrat. Again, the differences being played up are quite large, so there’s little risk of making too much out of a small difference. It’s good to know just how much of a difference makes a difference, though.

That said, neither Pew nor the Vox story mentions the very strong agreement between the different groups supporting opposing party candidates when the focus is on the relative magnitudes of agreement on aligned issues. Survey research typically focuses, of course, on percentages of responses to individual questions. Only measurement geeks like me wonder whether questions addressing a common theme could be related in a way that might convey more information. My curiosity was piqued, even though it is impossible to properly evaluate a model of this kind from the mere summary percentages. I knew if I found any correspondences they might just be accidents or coincidences, but I wanted to see what would happen.

So I typed up the text of the 18 issues concerning the seriousness of the problems being confronted in the US today, along with the percentages of registered voters saying each is a “very big” problem today. I put it all into SPSS and made a few technical checks to see if any major problems of interpretation would emerge from the nonlinear and ordinal percentages. The plots and correlations I did indicated that the same general results could be inferred from both the Pew percentages and their logit transformations.

While I was looking at a scatter plot of the Republican vs Democrat agreement percentages I noticed something interesting. I had been wondering if perhaps the striking differences in the groups’ willingness to say problems were serious might be a matter of relative emphases. Might the Republican supporters be less willing to find anything a big problem, but to nonetheless rank the issues in the same order as the Democrat supporters? This is, after all, exactly the kind of pattern commonly found in data from various surveys, assessments, and tests. No matter whether a respondent scores low overall, or scores high, the relative order of things stays the same.

Now, this is true in the kind of data I work with because considerable care is invested in composing questions that are intended to hang together like that. The idea is to deliberately vary the agreeability or difficulty of the questions so they all tap the same basic construct and demonstrably measure the same thing. When these kind of data are obtained, different questions measuring the same thing can be asked of different people without compromising the unit of measurement. That is, each different examinee or respondent can answer a unique set of questions and still have a measure comparable with anyone else’s. Like I said, this does not just happen by itself, but has to come about through a careful process of design and calibration. But the basic principles are well-established as being of longstanding and proven value across wide areas of research and practice.

So I was wondering if there might be one or more subsets of questions in the Pew data that would define the same problem magnitude dimension for supporters of both Republican and Democratic candidates. And as soon as I looked at the scatterplot of the percentages from the two groups, I saw that yes, indeed, there appeared to be four groups of issues that lined up along shared slopes. A color-coded version of that plot is in Figure 1.

The one statistical inference problem that emerged in examining these ordinal data concerns the yellow dot that is lowest and furthest to the left. At 8% agreement from the Republican supporters it was pulled away from the linear relation further than the other correspondences. When transformed into a log-odds unit, that single problematic difference lines up well with the other yellow dots further to the right.

The identity line in the figure shows where exact agreement between the two groups would be. That line marks out the connection between the same percentages of respondents agreeing an issue is a “very big” problem. We can see that the three green dots very nearly fall on that identity line. Just below them is a row of blue dots almost parallel with the identity line. Then there’s a third row of yellow dots further down, indicating more absolute disagreement between the two groups on these issues, but also showing a quite strong agreement as to their relative magnitudes within that group. Finally, there is another, red, line of dots in the lower right corner of the figure that marks out a more extreme range of absolute disagreement, but is also quite parallel to the identity line.

Fisher2018PewFig1

Figure 1 Initial plot of Republican vs Democrat Percentages agreement as to “Very Big” problems

Figures 2-5 below illustrate each of these groups of issues separately, giving further information on the problems and showing the regression lines and correlations for each contrast. The same colors have been retained to aid in seeing which groups of issues in Figure 1 are being shown.

The four areas of problems seem to me to correspond to issues of perceived major threats (Figure 2), accountability and access issues (Figure 3), equal opportunity issues (Figure 4), and systemic problems (Figure 5). Each of these content areas could be explored conceptually and qualitatively to assess whether some initial sense of a measured construct can be formed. If the by-person individual response data could be analyzed for fit to a proper measurement model, a much better job of determining the presence of invariant structure could be done.

But even without undertaking that work, these results already suggest a basis for productive conversations between the supposedly polarized groups. To start from the low-hanging fruit, the three problems the two groups agree on to within a couple of sampling errors (Figure 2) present topics of common agreement. Both Democrats and Republicans identify violent crime, the federal budget deficit, and drug addiction as matters of equally shared concern. The point is not that these are the highest rated problems for either group, but, rather, that they agree within the limits of statistical precision as to the extent that these are “very big” problems. It may be that setting shared priorities for addressing these problems could ground new relationships in that experience of having accomplished something productive together.

This new approach to building social capital might then proceed by taking up progressively more difficult areas of disagreement as to what “very big” problems are. Even though Republicans rate each area as less likely to be a “very big” problem, within each of the four groups of issues, they agree with Democrats as to their relative magnitudes. News like this might not sell a lot of ads, but it does offer hope for finding new ways of approaching relationships and crossing divides.

Fisher2018PewFig2

Figure 2.Republican vs Democrat areas of agreement as to “Very Big” problems

Fisher2018PewFig3

Figure 3 Republican vs Democrat areas of some disagreement as to “Very Big” problems

Fisher2018PewFig4

Figure 4 Republican vs Democrat areas of marked disagreement as to “Very Big” problems

Fisher2018PewFig5

Figure 5 Republican vs Democrat areas of fundamental disagreement as to “Very Big” problems

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Why economic growth can and inevitably will be green

October 1, 2018

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

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

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

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

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

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

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

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

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

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

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

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

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

 

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Common currencies for the exchange of human, social, and environmental value

October 1, 2018

I was just now reading an article (see link below) that underscores my conviction that the secure ledger platforms are the real message, and that cryptocurrencies are intuitions of the need for fungible expressions of scientifically and meaningfully measured human, social, and environmental value.

We absolutely need efficient markets to be able to buy, invest in, profit from, and scale up UN SDG sustainability products like carbon sequestration, reduced violence, and improved literacy rates. Linking real value with common product definitions and financial value will be complex, multilevel, and multifaceted, but it can be done. It will be expensive to create efficient markets for economically self-sustaining sustainability impacts, but doing so will pay returns many times greater than what’s invested. And neither doing nothing nor continuing as we are can stand as viable options.

When the right combination is hit, watch out! This event will reveal the Internet’s true purpose. Some will say it fulfills humanity’s destiny as stewards of the earth.

The economic transformation that follows will make everything that’s happened to date pale in comparison. It will become impossible to generate financial profits while destroying human, social, or environmental value. The alignment of financial and genuine wealth will even out monetary flows in such a way as to make a guaranteed minimum income nothing more than an obvious and inarguable consequence of economic reality. Critical engagement will lead sometimes to systemic improvements, sometimes to clear refutation of the critic, sometimes to a recognized need for more information, and more often to a new tolerance and respect for differences of opinion as our capacities to learn from one another grow.

All that to say I remain unconvinced by stories like this one that seem blind to the poetry, beauty, meaning, and power of taking living language as a model for adaptive, intelligent institutions capable of improving the human condition:

She prosecuted Bitcoin crimes. Now she’s a major cryptocurrency investor. – FORTUNE

For more on these matters, see previous posts here, my web site, my publications, etc.


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