Archive for the ‘Media’ Category

Excellent articulation of the rationale for living capital metrics 

November 2, 2017

I just found the best analysis of today’s situation I’ve seen yet. And it explicitly articulates and substantiates all my reasons for doing the work I’m doing. Wonderful to have this independent source of validation.

The crux of the problem is spelled out at the end of the article, where the degree of polarizing opposition is so extreme that standards of truth and evidence are completely compromised. My point is that the fact will remain, however, that everyone still uses language, and language still requires certain connections between concepts, words, and things to function. Continuing to use language in everyday functions in ways that assume a common consensus on meaningful reference may eventually come to be unbearably inconsistent with the way language is used politically, creating a social vacuum that will be filled by a new language capable of restoring the balance of meaning in the word-concept-thing triangles.

As is repeatedly argued in this blog, my take is that what we are witnessing is language restructuring itself to incorporate new degrees of complexity at a general institutional, world historic level. The falsehoods of our contemporary institutional definitions of truth and fact are rooted in the insufficiencies of the decision making methods and tools widely used in education, health care, government, business, etc. The numbers called measures are identified using methods that almost universally ignore the gifts of self-organized meaning that offer themselves in the structure of test, assessment, survey, poll, and evaluation response data. Those shortcomings in our information infrastructure and communication systems are causing negative feedback loops of increasingly chaotic noise.

This is why it is so important that precision science is rooted in everyday language and thinking, per Nersessian’s (2002) treatment of Maxwell and Rasch’s (1960, pp. 110-115) adoption of Maxwell’s method of analogy (Fisher, 2010; Fisher & Stenner, 2013). The metric system (System International des Unites, or SI) is a natural language extension of intuitive and historical methods of bringing together words, concepts, and things, renamed instruments, theories, and data. A new SI for human, social, and natural capital built out into science and commerce will be one component of a multilevel and complex adaptive system that resolves today’s epistemic crisis by tapping deeper resources for the creation of meaning than are available in today’s institutions.

Everything is interrelated. The epistemic crisis will be resolved when our institutions base decisions not just on a potentially arbitrary collection of facts but on facts internally consistent enough to support instrument calibration and predictive theory. The facts have to be common sensical to everyday people, to employees, customers, teachers, students, patients, doctors, nurses, managers. People have to be able to see themselves and where they stand relative to their goals, their origins, and everyone else in the pictures drawn by the results of tests, surveys, and evaluations. That’s not possible in today’s systems. And in those systems, some people have systematically unfair advantages. That has to change, not through some kind of Brave New World hobbling of those with advantages but by leveling the playing field to allow everyone the same opportunities for self-improvement and the rewards that follow from it.

That’s it in a nutshell. Really good article:

America is facing an epistemic crisis – Vox

https://apple.news/A0alOElOQT5itYGPAJ3eYPQ

References

Fisher, W. P., Jr. (2010, June 13-16). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Chair), Https://conference.cbs.dk/index.php/rasch/Rasch2010/paper/view/824. Probabilistic models for measurement in education, psychology, social science and health: Celebrating 50 years since the publication of Rasch’s Probabilistic Models, University of Copenhagen School of Business, FUHU Conference Centre, Copenhagen, Denmark.

Fisher, W. P., Jr. (2010). The standard model in the history of the natural sciences, econometrics, and the social sciences. Journal of Physics Conference Series, 238(1), http://iopscience.iop.org/1742-6596/238/1/012016/pdf/1742-6596_238_1_012016.pdf.

Fisher, W. P., Jr., & 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.

Nersessian, N. J. (2002). Maxwell and “the method of physical analogy”: Model-based reasoning, generic abstraction, and conceptual change. In D. Malament (Ed.), Reading natural philosophy: Essays in the history and philosophy of science and mathematics (pp. 129-166). Lasalle, Illinois: Open Court.

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

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Economy of language, Eros, meaning, the public, and its problems

July 11, 2017

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

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

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

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

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

Measuring Instruments as Media for the Expression of Creative Passions in Education

June 26, 2015

Measurement is often viewed as a reduction of complex phenomena to numbers. It is accordingly also often conceived as mechanical, and disconnected from the world of life. Educational examinations are seen by many as an especially egregious form of inappropriate reduction. This perspective is contradicted, however, by a perspective that sees an analogy between educational assessment and music. Calibrated instruments, mathematical scales, and high technology play key roles in the production of music, which, ironically, is widely considered the most alive, captivating and emotionally powerful of the arts. Though behavioral psychology has indeed learned how to use music to manipulate consumer purchasing decisions, music is unabashedly accepted nonetheless as the highest expression of passion in art.

The question then arises as to if and how measurement in other areas, such as in education, might be conceived, designed, and practiced as a medium for the expression and fulfillment of creative passions. Key issues involved in substantively realizing a musical metaphor in human and social measurement include capacities to tune instruments, to define common scales, to score performances, to orchestrate harmonious relationships, to enhance choral grace note effects, and to combine elements in unique but pleasing and recognizable rhythmic arrangements.

Practical methods for making educational measurement the medium for the expression of creative passions for learning are in place in thousands of schools nationally and internationally. With such tools in hand, formative applications of integrated instruction and assessment could be conceived as intuitive media for composing and conducting expressions of creative passions. Student outcomes in reading, mathematics, and other domains may then come to be seen in terms of portfolios of works akin to those produced by musicians, sculptors, film makers, or painters.

Hundreds of thousands of books and millions of articles tuned to the same text complexity scale, for instance, provide readers an extensive palette of colorful tones and timbres for expressing their desires and capacities for learning. Graphical presentations of individual students’ outcomes, as well as outcomes aggregated by classroom, school, district, etc., could be presented, interpreted and experienced as public performances of artful developmental narratives enabling dramatic performances of personal uniqueness and social generality.

Measurement instrumentation in education is able to capture, aggregate, and organize literacy, numeracy, socio-emotional intelligence, and other performances into special portfolios documenting the play and dance of emerging new understandings. As in any creative process, accidents, errors, and idiosyncratic patterns of strengths and weaknesses may evoke powerful and dramatic expressions of beauty, and human and social value. And just as members of musical ensembles may complement one another’s skills, using rhythm and harmony to improve each others’ playing abilities in practice, so, too, instruments of formative assessment tuned to the same scale can be used to coordinate and enhance individual student and teacher skill levels.

Possibilities for orchestrating such performances across educational, health care, social service, environmental management, and other fields could similarly take advantage of existing instrument calibration and measurement technologies.

Science, Public Goods, and the Monetization of Commodities

August 13, 2011

Though I haven’t read Philip Mirowski’s new book yet (Science-Mart: Privatizing American Science. Cambridge, MA: Harvard University Press, 2011), a statement in the cover blurb given at Amazon.com got me thinking. I can’t help but wonder if there is another way of interpreting neoliberal ideology’s “radically different view of knowledge and discovery: [that] the fruits of scientific investigation are not a public good that should be freely available to all, but are commodities that could be monetized”?

Corporations and governments are not the only ones investing in research and new product development, and they are not the only ones who could benefit from the monetization of the fruits of scientific investigation. Individuals make these investments as well, and despite ostensible rights to private ownership, no individuals anywhere have access to universally comparable, uniformly expressed, and scientifically valid information on the quantity or quality of the literacy, health, community, or natural capital that is rightfully theirs. They accordingly also then do not have any form of demonstrable legal title to these properties. In the same way that corporations have successfully advanced their economic interests by seeing that patent and intellectual property laws were greatly strengthened, so, too, ought individuals and communities advance their economic interests by, first, expanding the scope of weights and measures standards to include intangible assets, and second, by strengthening laws related to the ownership of privately held stocks of living capital.

The nationalist and corporatist socialization of research will continue only as long as social capital, human capital, and natural capital are not represented in the universally uniform common currencies and transparent media that could be provided by an intangible assets metric system. When these forms of capital are brought to economic life in fungible measures akin to barrels, bushels, or kilowatts, then they will be monetized commodities in the full capitalist sense of the term, ownable and purchasable products with recognizable standard definitions, uniform quantitative volumes, and discernable variations in quality. Then, and only then, will individuals gain economic control over their most important assets. Then, and only then, will we obtain the information we need to transform education, health care, social services, and human and natural resource management into industries in which quality is appropriately rewarded. Then, and only then, will we have the means for measuring genuine progress and authentic wealth in ways that correct the insufficiencies of the GNP/GDP indexes.

The creation of efficiently functioning markets for all forms of capital is an economic, political, and moral necessity (see Ekins, 1992 and others). We say we manage what we measure, but very little effort has been put into measuring (with scientific validity and precision in universally uniform and accessible aggregate terms) 90% of the capital resources under management: human abilities, motivations, and health; social commitment, loyalty, and trust; and nature’s air and water purification and ecosystem services (see Hawken, Lovins, & Lovins, 1999, among others). All human suffering, sociopolitical discontent, and environmental degradation are rooted in the same common cause: waste (see Hawken, et al., 1999). To apply lean thinking to removing the wasteful destruction of our most valuable resources, we must measure these resources in ways that allow us to coordinate and align our decisions and behaviors virtually, at a distance, with no need for communicating and negotiating the local particulars of the hows and whys of our individual situations. For more information on these ideas, search “living capital metrics” and see works like the following:

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

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

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

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

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

Miller, P., & O’Leary, T. (2007). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-34.

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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.

Enchantment, Organizations, and Mediating Instruments: Potential for a New Consensus?

August 3, 2011

I just came across something that could be helpful in regaining some forward momentum and expanding the frame of reference for the research on caring in nursing with Jane Sumner (Sumner & Fisher, 2008). We have yet to really work in the failure of Habermas’ hermeneutic objectivism (Kim, 2002; Thompson, 1984) and we haven’t connected what we’ve done with (a) Ricoeur’s (1984, 1985, 1990, 1995) sense of narrative as describing the past en route to prescribing the future (prefiguring, configuring, and refiguring the creation of meaning in discourse) and with (b) Wright’s (1999) sense of learning from past data to efficiently and effectively anticipate new data within a stable inferential frame of reference.

Now I’ve found a recent publication that resonates well with this goal, and includes examples from nursing to boot. Boje and Baskin (2010; see especially pp. 12-17 in the manuscript available at http://peaceaware.com/vita/paper_pdfs/JOCM_Never_Disenchanted.pdf) cite only secondary literature but do a good job of articulating where the field is at conceptually and in tracing the sources of that articulation.  So they make no mention of Ricoeur on narrative (1984, 1985, 1990) and on play and the heuristic fiction (1981, pp. 185-187), and they make no mention of Gadamer on play as the most important clue to methodological authenticity (1989, pp. 101-134). It follows that they then also do not make any use of the considerable volume of other available and relevant work on the metaphysics of allure, captivation, enthrallment, rapture, beauty, or eros.

This is all very important because these issues are highly salient markers of the distinction between a modern, Cartesian, and mechanical worldview destructive of enchantment and play, and the amodern, nonCartesian, and organic worldview in tune with enchantment and play. As I have stressed repeatedly in these posts, the way we frame problems is now the primary problem, in opposition to those who think identifying and applying resources, techniques, or will power is the problem. It is essential that we learn to frame problems in a way that begins from requirements of subject-object interdependence instead of from assumptions of subject-object independence. Previous posts here explore in greater detail how we are all captivated by the desire for meaning. Any time we choose negotiation or patient waiting over violence, we express faith in the ultimate value of trusting our words. So though Boje and Baskin do not document this larger context, they still effectively show exactly where and how work in the nonCartesian paradigm of enchantment connects up with what’s going on in organizational change management theory.

The paper’s focus on narrative as facilitating enchantment and disenchantment speaks to our fundamental absorption into the play of language. Enchantment is described on page 2 as involving positive connection with existence, of being enthralled with the wonder of being endowed with natural and cultural gifts.  Though not described as such, this hermeneutics of restoration, as Ricoeur (1967) calls it, focuses on the way symbols give rise to thought in an unasked-for assertion of meaningfulness. The structure we see emerge of its own accord across multiple different data sets from tests, surveys, and assessments is an important example of this gift through which previously identified meanings re-assert themselves anew (see my published philosophical work, such as Fisher, 2004). The contrast with disenchantment of course arises as a function of the dead and one-sided modern Cartesian effort aimed at controlling the environment, which effectively eliminates wonder and meaning via a hermeneutics of suspicion.

In accord with the work done to date with Sumner on caring in nursing, the Boje and Baskin paper describes people’s variable willingness to accept disenchantment or demand enchantment (p. 13) in terms that look quite like preconventional and postconventional Kohlbergian stages. A nurse’s need to shift from one dominant narrative form to another is described as very difficult because of the way she had used the one to which she was accustomed to construct her identity as a nurse (p. 15). Bi-directionality between nurses and patients is implied in another example of a narrative shift in a hospital (p. 16). Both identity and bi-directionality are central issues in the research with Sumner.

The paper also touches on the conceptual domain of instrumental realism, as this is developed in the works of Ihde, Latour, Heelan and others (on p. 6; again, without citing them), and emphasizes a nonCartesian subject-object unity and belongingness, which is described at length in Ricoeur’s work. At the bottom of page 7 and top of 8, storytelling is theorized in terms of retrospection, presentness, and a bet on future meaning, which precisely echoes Ricoeur’s (1984, 1985, 1990) sense of narrative refiguration, configuration, and prefiguration. A connection with measurement comes here, in that what we want is to:

“reach beyond the data in hand to what these data might imply about future data, still unmet, but urgent to foresee. The first problem is how to predict values for these future data, which, by the meaning of inference, are necessarily missing. This meaning of missing must include not only the future data to be inferred but also all possible past data that were lost or never collected” (Wright, 1999, p. 76).

Properly understood and implemented (see previous posts in this blog), measurement based in models of individual behavior provides a way to systematically create an atmosphere of emergent enchantment. Having developmentally sound narratives rooted in individual measures on multiple dimensions over time gives us a shared written history that we can all find ourselves in, and that we can then use to project a vision of a shared future that has reasonable expectations for what’s possible.

This mediation of past and future by means of technical instruments is being described in a way (Miller & O’Leary, 2007) that to me (Fisher & Stenner, 2011) denotes a vital distinction not just between the social and natural sciences, but between economically moribund and inflationary industries such as education, health care, and social services, on the one hand, and economically vibrant and deflationary industries such as microprocessors, on the other.

It is here, and I say this out loud for the first time here, even to myself, that I begin to see the light at the end of the tunnel, to see a way that I might find a sense of closure and resolution in the project I took up over 30 years ago. My puzzle has been one of understanding in theory and practice how it is that measurement and mathematical thinking are nothing but refinements of the logic used in everyday conversation. It only occurs to me now that, if we can focus the conversations that we are in ways that balance meaningfulness and precision, that situate each of us as individuals relative to the larger wholes of who we have been and who we might be, that encompasses both the welcoming Socratic midwife and the annoying Socratic gadfly as different facets of the same framework, and that enable us to properly coordinate and align technical projects involving investments in intangible capital, well, then, we’ll be in a position to more productively engage with the challenges of the day.

There won’t be any panacea but there will be a new consensus and a new infrastructure that, however new they may seem, will enact yet again, in a positive way, the truth of the saying, “the more things change, the more they stay the same.” As I’ve repeatedly argued, the changes we need to implement are nothing but extensions of age-old principles into areas in which they have not yet been applied. We should take some satisfaction from this, as what else could possibly work? The originality of the application does not change the fact that it is rooted in appropriating, via a refiguration, to be sure, a model created for other purposes that works in relation to new purposes.

Another way of putting the question is in terms of that “permanent arbitration between technical universalism and the personality constituted on the ethico-political plane” characteristic of the need to enter into the global technical society while still retaining our roots in our cultural past (Ricoeur, 1974, p. 291). What is needed is the capacity to mediate each individual’s retelling of the grand narrative so that each of us sees ourselves in everyone else, and everyone else in ourselves. Though I am sure the meaning of this is less than completely transparent right now, putting it in writing is enormously satisfying, and I will continue to work on telling the tale as it needs to be told.

 References

Boje, D., & Baskin, K. (2010). Our organizations were never disenchanted: Enchantment by design narratives vs. enchantment by emergence. Journal of Organizational Change Management, 24(4), 411-426.

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

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. International Measurement Confederation (IMEKO). Jena, Germany.

Gadamer, H.-G. (1989). Truth and method (J. Weinsheimer & D. G. Marshall, Trans.) (Second revised edition). New York: Crossroad.

Kim, K.-M. (2002, May). On the failure of Habermas’s hermeneutic objectivism. Cultural Studies <–> Critical Methodologies, 2(2), 270-98.

Miller, P., & O’Leary, T. (2007, October/November). Mediating instruments and making markets: Capital budgeting, science and the economy. Accounting, Organizations, and Society, 32(7-8), 701-34.

Ricoeur, P. (1967). Conclusion: The symbol gives rise to thought. In R. N. Anshen (Ed.), The symbolism of evil (pp. 347-57). Boston, Massachusetts: Beacon Press.

Ricoeur, P. (1974). Political and social essays (D. Stewart & J. Bien, Eds.). Athens, Ohio: Ohio University Press.

Ricoeur, P. (1981). Hermeneutics and the human sciences: Essays on language, action and interpretation (J. B. Thompson, Ed.) (J. B. Thompson, Trans.). Cambridge, England: Cambridge University Press.

Ricoeur, P. (1984, 1985, 1990). Time and Narrative, Vols. 1-3 (K. McLaughlin (Blamey) & D. Pellauer, Trans.). Chicago, Illinois: University of Chicago Press.

Ricoeur, P. (1995). Reply to Peter Kemp. In L. E. Hahn (Ed.), The philosophy of Paul Ricoeur (pp. 395-398). Chicago, Illinois: Open Court.

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

Thompson, J. B. (1981). Critical hermeneutics: A study in the thought of Paul Ricoeur and Jurgen Habermas. New York: Cambridge University Press.

Wright, B. D. (1999). Fundamental measurement for psychology. In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every educator and psychologist should know (pp. 65-104 [http://www.rasch.org/memo64.htm]). Hillsdale, New Jersey: Lawrence Erlbaum Associates.

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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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A Framework for Competitive Advantage in Managing Intangible Assets

July 26, 2011

It has long been recognized that externalities like social costs could be brought into the market should ways of measuring them objectively be devised. Markets, however, do not emerge spontaneously from the mere desire to be able to buy and sell; they are, rather, the products of actors and agencies that define the rules, roles, and relationships within which transaction costs are reduced and from which value, profits, and authentic wealth may be extracted. Objective measurement is necessary to reduced transaction costs but is by itself insufficient to the making of markets. Thus, markets for intangible assets, such as human, social, and natural capital, remain inefficient and undeveloped even though scientific theories, models, methods, and results demonstrating their objective measurability have been available for over 80 years.

Why has the science of objectively measured intangible assets not yet led to efficient markets for those assets? The crux of the problem, the pivot point at which an economic Archimedes could move the world of business, has to do with verifiable trust. It may seem like stating the obvious, but there is much to be learned from recognizing that shared narratives of past performance and a shared vision of the future are essential to the atmosphere of trust and verifiability needed for the making of markets. The key factor is the level of detail reliably tapped by such narratives.

For instance, some markets seem to have the weight of an immovable mass when the dominant narrative describes a static past and future with no clearly defined trajectory of leverageable development. But when a path of increasing technical capacity or precision over time can be articulated, entrepreneurs have the time frames they need to be able to coordinate, align, and manage budgeting decisions vis a vis investments, suppliers, manufacturers, marketing, sales, and customers. For example, the building out of the infrastructure of highways, electrical power, and water and sewer services assured manufacturers of automobiles, appliances, and homes that they could develop products for which there would be ready customers. Similarly, the mapping out of a path of steady increases in technical precision at no additional cost in Moore’s Law has been a key factor enabling the microprocessor industry’s ongoing history of success.

Of course, as has been the theme of this blog since day one, similar paths for the development of new infrastructural capacities could be vital factors for making new markets for human, social, and natural capital. I’ll be speaking on this topic at the forthcoming IMEKO meeting in Jena, Germany, August 31 to September 2. Watch this spot for more on this theme in the near future.

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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.

The Moral Implications of the Concept of Human Capital: More on How to Create Living Capital Markets

March 22, 2011

The moral reprehensibility of the concept of human capital hinges on its use in rationalizing impersonal business decisions in the name of profits. Even when the viability of the organization is at stake, the discarding of people (referred to in some human resource departments as “taking out the trash”) entails degrees of psychological and economic injury no one should have to suffer, or inflict.

There certainly is a justified need for a general concept naming the productive capacity of labor. But labor is far more than a capacity for work. No one’s working life should be reduced to a job description. Labor involves a wide range of different combinations of skills, abilities, motivations, health, and trustworthiness. Human capital has then come to be broken down into a wide variety of forms, such as literacy capital, health capital, social capital, etc.

The metaphoric use of the word “capital” in the phrase “human capital” referring to stocks of available human resources rings hollow. The traditional concept of labor as a form of capital is an unjustified reduction of diverse capacities in itself. But the problem goes deeper. Intangible resources like labor are not represented and managed in the forms that make markets for tangible resources efficient. Transferable representations, like titles and deeds, give property a legal status as owned and an economic status as financially fungible. And in those legal and economic terms, tangible forms of capital give capitalism its hallmark signification as the lifeblood of the cycle of investment, profits, and reinvestment.

Intangible forms of capital, in contrast, are managed without the benefit of any standardized way of proving what is owned, what quantity or quality of it exists, and what it costs. Human, social, and natural forms of capital are therefore managed directly, by acting in an unmediated way on whomever or whatever embodies them. Such management requires, even in capitalist economies, the use of what are inherently socialistic methods, as these are the only methods available for dealing with the concrete individual people, communities, and ecologies involved (Fisher, 2002, 2011; drawing from Hayek, 1948, 1988; De Soto, 2000).

The assumption that transferable representations of intangible assets are inconceivable or inherently reductionist is, however, completely mistaken. All economic capital is ultimately brought to life (conceived, gestated, midwifed, and nurtured to maturity) as scientific capital. Scientific measurability is what makes it possible to add up the value of shares of stock across holdings, to divide something owned into shares, and to represent something in a court or a bank in a portable form (Latour, 1987; Fisher, 2002, 2011).

Only when you appreciate this distinction between dead and living capital, between capital represented on transferable instruments and capital that is not, then you can see that the real tragedy is not in the treatment of labor as capital. No, the real tragedy is in the way everyone is denied the full exercise of their rights over the skills, abilities, health, motivations, trustworthiness, and environmental resources that are rightly their own personal, private property.

Being homogenized at the population level into an interchangeable statistic is tragic enough. But when we leave the matter here, we fail to see and to grasp the meaning of the opportunities that are lost in that myopic world view. As I have been at pains in this blog to show, statistics are not measures. Statistical models of interactions between several variables at the group level are not the same thing as measurement models of interactions within a single variable at the individual level. When statistical models are used in place of measurement models, the result is inevitably numbers without a soul. When measurement models of individual response processes are used to produce meaningful estimates of how much of something someone possesses, a whole different world of possibilities opens up.

In the same way that the Pythagorean Theorem applies to any triangle, so, too, do the coordinates from the international geodetic survey make it possible to know everything that needs to be known about the location and disposition of a piece of real estate. Advanced measurement models in the psychosocial sciences are making it possible to arrive at similarly convenient and objective ways of representing the quality and quantity of intangible assets. Instead of being just one number among many others, real measures tell a story that situates each of us relative to everyone else in a meaningful way.

The practical meaning of the maxim “you manage what you measure” stems from those instances in which measures embody the fullness of the very thing that is the object of management interest. An engine’s fuel efficiency, or the volume of commodities produced, for instance, are things that can be managed less or more efficiently because there are measures of them that directly represent just what we want to control. Lean thinking enables the removal of resources that do not contribute to the production of the desired end result.

Many metrics, however, tend to obscure and distract from what need to be managed. The objects of measurement may seem to be obviously related to what needs to be managed, but dealing with each of them piecemeal results in inefficient and ineffective management. In these instances, instead of the characteristic cycle of investment, profit, and reinvestment, there seems only a bottomless pit absorbing ever more investment and never producing a profit. Why?

The economic dysfunctionality of intangible asset markets is intimately tied up with the moral dysfunctionality of those markets. Drawing an analogy from a recent analysis of political freedom (Shirky, 2010), economic freedom has to be accompanied by a market society economically literate enough, economically empowered enough, and interconnected enough to trade on the capital stocks issued. Western society, and increasingly the entire global society, is arguably economically literate and sufficiently interconnected to exercise economic freedom.

Economic empowerment is another matter entirely. There is no economic power without fungible capital, without ways of representing resources of all kinds, tangible and intangible, that transparently show what is available, how much of it there is, and what quality it is. A form of currency expressing the value of that capital is essential, but money is wildly insufficient to the task of determining the quality and quantity of the available capital stocks.

Today’s education, health care, human resource, and environmental quality markets are the diametric opposite of the markets in which investors, producers, and consumers are empowered. Only when dead human, social, and natural capital is brought to life in efficient markets (Fisher, 2011) will we empower ourselves with fuller degrees of creative control over our economic lives.

The crux of the economic empowerment issue is this: in the current context of inefficient intangibles markets, everyone is personally commodified. Everything that makes me valuable to an employer or investor or customer, my skills, motivations, health, and trustworthiness, is unjustifiably reduced to a homogenized unit of labor. And in the social and environmental quality markets, voting our shares is cumbersome, expensive, and often ineffective because of the immense amount of work that has to be done to defend each particular living manifestation of the value we want to protect.

Concentrated economic power is exercised in the mass markets of dead, socialized intangible assets in ways that we are taught to think of as impersonal and indifferent to each of us as individuals, but which is actually experienced by us as intensely personal.

So what is the difference between being treated personally as a commodity and being treated impersonally as a commodity? This is the same as asking what it would mean to be empowered economically with creative control over the stocks of human, social, and natural capital that are rightfully our private property. This difference is the difference between dead and living capital (Fisher, 2002, 2011).

Freedom of economic communication, realized in the trade of privately owned stocks of any form of capital, ought to be the highest priority in the way we think about the infrastructure of a sustainable and socially responsible economy. For maximum efficiency, that freedom requires a common meaningful and rigorous quantitative language enabling determinations of what exactly is for sale, and its quality, quantity, and unit price. As I have ad nauseum repeated in this blog, measurement based in scientifically calibrated instrumentation traceable to consensus standards is absolutely essential to meeting this need.

Coming in at a very close second to the highest priority is securing the ability to trade. A strong market society, where people can exercise the right to control their own private property—their personal stocks of human, social, and natural capital—in highly efficient markets, is more important than policies, regulations, and five-year plans dictating how masses of supposedly homogenous labor, social, and environmental commodities are priced and managed.

So instead of reacting to the downside of the business cycle with a socialistic safety net, how might a capitalistic one prove more humane, moral, and economically profitable? Instead of guaranteeing a limited amount of unemployment insurance funded through taxes, what we should have are requirements for minimum investments in social capital. Instead of employment in the usual sense of the term, with its implications of hiring and firing, we should have an open market for fungible human capital, in which everyone can track the price of their stock, attract and make new investments, take profits and income, upgrade the quality and/or quantity of their stock, etc.

In this context, instead of receiving unemployment compensation, workers not currently engaged in remunerated use of their skills would cash in some of their accumulated stock of social capital. The cost of social capital would go up in periods of high demand, as during the recent economic downturns caused by betrayals of trust and commitment (which are, in effect, involuntary expenditures of social capital). Conversely, the cost of human capital would also fluctuate with supply and demand, with the profits (currently referred to as wages) turned by individual workers rising and falling with the price of their stocks. These ups and downs, being absorbed by everyone in proportion to their investments, would reduce the distorted proportions we see today in the shares of the rewards and punishments allotted.

Though no one would have a guaranteed wage, everyone would have the opportunity to manage their capital to the fullest, by upgrading it, keeping it current, and selling it to the highest bidder. Ebbing and flowing tides would more truly lift and drop all boats together, with the drops backed up with the social capital markets’ tangible reassurance that we are all in this together. This kind of a social capitalism transforms the supposedly impersonal but actually highly personal indifference of flows in human capital into a more fully impersonal indifference in which individuals have the potential to maximize the realization of their personal goals.

What we need is to create a visible alternative to the bankrupt economic system in a kind of reverse shock doctrine. Eleanor Roosevelt often said that the thing we are most afraid of is the thing we most need to confront if we are to grow. The more we struggle against what we fear, the further we are carried away from what we want. Only when we relax into the binding constraints do we find them loosened. Only when we channel overwhelming force against itself or in a productive direction can we withstand attack. When we find the courage to go where the wild things are and look the monsters in the eye will we have the opportunity to see if their fearful aspect is transformed to playfulness. What is left is often a more mundane set of challenges, the residuals of a developmental transition to a new level of hierarchical complexity.

And this is the case with the moral implications of the concept of human capital. Treating individuals as fungible commodities is a way that some use to protect themselves from feeling like monsters and from being discarded as well. Those who find themselves removed from the satisfactions of working life can blame the shortsightedness of their former colleagues, or the ugliness of the unfeeling system. But neither defensive nor offensive rationalizations do anything to address the actual problem, and the problem has nothing to do with the morality or the immorality of the concept of human capital.

The problem is the problem. That is, the way we approach and define the problem delimits the sphere of the creative options we have for solving it. As Henry Ford is supposed to have said, whether you think you can or you think you cannot, you’re probably right. It is up to us to decide whether we can create an economic system that justifies its reductions and actually lives up to its billing as impersonal and unbiased, or if we cannot. Either way, we’ll have to accept and live with the consequences.

References

DeSoto, H. (2000). The mystery of capital: Why capitalism triumphs in the West and fails everywhere else. New York: Basic Books.

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

Fisher, W. P., Jr. (2011, Spring). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), in press.

Hayek, F. A. (1948). Individualism and economic order. Chicago: University of Chicago Press.

Hayek, F. A. (1988). The fatal conceit: The errors of socialism (W. W. Bartley, III, Ed.) The Collected Works of F. A. Hayek. Chicago: University of Chicago Press.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Shirky, C. (2010, December 20). The political power of social media: Technology, the public sphere, and political change. Foreign Affairs, 90(1), http://www.foreignaffairs.com/articles/67038/clay-shirky/the-political-power-of-social-media.

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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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How Evidence-Based Decision Making Suffers in the Absence of Theory and Instrument: The Power of a More Balanced Approach

January 28, 2010

The Basis of Evidence in Theory and Instrument

The ostensible point of basing decisions in evidence is to have reasons for proceeding in one direction versus any other. We want to be able to say why we are proceeding as we are. When we give evidence-based reasons for our decisions, we typically couch them in terms of what worked in past experience. That experience might have been accrued over time in practical applications, or it might have been deliberately arranged in one or more experimental comparisons and tests of concisely stated hypotheses.

At its best, generalizing from past experience to as yet unmet future experiences enables us to navigate life and succeed in ways that would not be possible if we could not learn and had no memories. The application of a lesson learned from particular past events to particular future events involves a very specific inferential process. To be able to recognize repeated iterations of the same things requires the accumulation of patterns of evidence. Experience in observing such patterns allows us to develop confidence in our understanding of what that pattern represents in terms of pleasant or painful consequences. When we are able to conceptualize and articulate an idea of a pattern, and when we are then able to recognize a new occurrence of that pattern, we have an idea of it.

Evidence-based decision making is then a matter of formulating expectations from repeatedly demonstrated and routinely reproducible patterns of observations that lend themselves to conceptual representations, as ideas expressed in words. Linguistic and cultural frameworks selectively focus attention by projecting expectations and filtering observations into meaningful patterns represented by words, numbers, and other symbols. The point of efforts aimed at basing decisions in evidence is to try to go with the flow of this inferential process more deliberately and effectively than might otherwise be the case.

None of this is new or controversial. However, the inferential step from evidence to decision always involves unexamined and unjustified assumptions. That is, there is always an element of metaphysical faith behind the expectation that any given symbol or word is going to work as a representation of something in the same way that it has in the past. We can never completely eliminate this leap of faith, since we cannot predict the future with 100% confidence. We can, however, do a lot to reduce the size of the leap, and the risks that go with it, by questioning our assumptions in experimental research that tests hypotheses as to the invariant stability and predictive utility of the representations we make.

Theoretical and Instrumental Assumptions Hidden Behind the Evidence

For instance, evidence as to the effectiveness of an intervention or treatment is often expressed in terms of measures commonly described as quantitative. But it is unusual for any evidence to be produced justifying that description in terms of something that really adds up in the way numbers do. So we often find ourselves in situations in which our evidence is much less meaningful, reliable, and valid than we suppose it to be.

Quantitative measures are often valued as the hallmark of rational science. But their capacity to live up to this billing depends on the quality of the inferences that can be supported. Very few researchers thoroughly investigate the quality of their measures and justify the inferences they make relative to that quality.

Measurement presumes a reproducible pattern of evidence that can serve as the basis for a decision concerning how much of something has been observed. It naturally follows that we often base measurement in counts of some kind—successes, failures, ratings, frequencies, etc. The counts, scores, or sums are then often transformed into percentages by dividing them into the maximum possible that could be obtained. Sometimes the scores are averaged for each person measured, and/or for each item or question on the test, assessment, or survey. These scores and percentages are then almost universally fed directly into decision processes or statistical analyses with no further consideration.

The reproducible pattern of evidence on which decisions are based is presumed to exist between the measures, not within them. In other words, the focus is on the group or population statistics, not on the individual measures. Attention is typically focused on the tip of the iceberg, the score or percentage, not on the much larger, but hidden, mass of information beneath it. Evidence is presumed to be sufficient to the task when the differences between groups of scores are of a consistent size or magnitude, but is this sufficient?

Going Past Assumptions to Testable Hypotheses

In other words, does not science require that evidence be explained by theory, and embodied in instrumentation that provides a shared medium of observation? As shown in the blue lines in the Figure below,

  • theory, whether or not it is explicitly articulated, inevitably influences both what counts as valid data and the configuration of the medium of its representation, the instrument;
  • data, whether or not it is systematically gathered and evaluated, inevitably influences both the medium of its representation, the instrument, and the implicit or explicit theory that explains its properties and justifies its applications; and
  • instruments, whether or not they are actually calibrated from a mapping of symbols and substantive amounts, inevitably influence data gathering and the image of the object explained by theory.

The rhetoric of evidence-based decision making skips over the roles of theory and instrumentation, drawing a direct line from data to decision. In leaving theory laxly formulated, we allow any story that makes a bit of sense and is communicated by someone with a bit of charm or power to carry the day. In not requiring calibrated instrumentation, we allow any data that cross the threshold into our awareness to serve as an acceptable basis for decisions.

What we want, however, is to require meaningful measures that really provide the evidence needed for instruments that exhibit invariant calibrations and for theories that provide predictive explanatory control over the variable. As shown in the Figure, we want data that push theory away from the instrument, theory that separates the data and instrument, and instruments that get in between the theory and data.

We all know to distrust too close a correspondence between theory and data, but we too rarely understand or capitalize on the role of the instrument in mediating the theory-data relation. Similarly, when the questions used as a medium for making observations are obviously biased to produce responses conforming overly closely with a predetermined result, we see that the theory and the instrument are too close for the data to serve as an effective mediator.

Finally, the situation predominating in the social sciences is one in which both construct and measurement theories are nearly nonexistent, which leaves data completely dependent on the instrument it came from. In other words, because counts of correct answers or sums of ratings are mistakenly treated as measures, instruments fully determine and restrict the range of measurement to that defined by the numbers of items and rating categories. Once the instrument is put in play, changes to it would make new data incommensurable with old, so, to retain at least the appearance of comparability, the data structure then fully determines and restricts the instrument.

What we want, though, is a situation in which construct and measurement theories work together to make the data autonomous of the particular instrument it came from. We want a theory that explains what is measured well enough for us to be able to modify existing instruments, or create entirely new ones, that give the same measures for the same amounts as the old instruments. We want to be able to predict item calibrations from the properties of the items, we want to obtain the same item calibrations across data sets, and we want to be able to predict measures on the basis of the observed responses (data) no matter which items or instrument was used to produce them.

Most importantly, we want a theory and practice of measurement that allows us to take missing data into account by providing us with the structural invariances we need as media for predicting the future from the past. As Ben Wright (1997, p. 34) said, any data analysis method that requires complete data to produce results disqualifies itself automatically as a viable basis for inference because we never have complete data—any practical system of measurement has to be positioned so as to be ready to receive, process, and incorporate all of the data we have yet to gather. This goal is accomplished to varying degrees in Rasch measurement (Rasch, 1960; Burdick, Stone, & Stenner, 2006; Dawson, 2004). Stenner and colleagues (Stenner, Burdick, Sanford, & Burdick, 2006) provide a trajectory of increasing degrees to which predictive theory is employed in contemporary measurement practice.

The explanatory and predictive power of theory is embodied in instruments that focus attention on recording observations of salient phenomena. These observations become data that inform the calibration of instruments, which then are used to gather further data that can be used in practical applications and in checks on the calibrations and the theory.

“Nothing is so practical as a good theory” (Lewin, 1951, p. 169). Good theory makes it possible to create symbolic representations of things that are easy to think with. To facilitate clear thinking, our words, numbers, and instruments must be transparent. We have to be able to look right through them at the thing itself, with no concern as to distortions introduced by the instrument, the sample, the observer, the time, the place, etc. This happens only when the structure of the instrument corresponds with invariant features of the world. And where words effect this transparency to an extent, it is realized most completely when we can measure in ways that repeatedly give the same results for the same amounts in the same conditions no matter which instrument, sample, operator, etc. is involved.

Where Might Full Mathematization Lead?

The attainment of mathematical transparency in measurement is remarkable for the way it focuses attention and constrains the imagination. It is essential to appreciate the context in which this focusing occurs, as popular opinion is at odds with historical research in this regard. Over the last 60 years, historians of science have come to vigorously challenge the widespread assumption that technology is a product of experimentation and/or theory (Kuhn, 1961/1977; Latour, 1987, 2005; Maas, 2001; Mendelsohn, 1992; Rabkin, 1992; Schaffer, 1992; Heilbron, 1993; Hankins & Silverman, 1999; Baird, 2002). Neither theory nor experiment typically advances until a key technology is widely available to end users in applied and/or research contexts. Rabkin (1992) documents multiple roles played by instruments in the professionalization of scientific fields. Thus, “it is not just a clever historical aphorism, but a general truth, that ‘thermodynamics owes much more to the steam engine than ever the steam engine owed to thermodynamics’” (Price, 1986, p. 240).

The prior existence of the relevant technology comes to bear on theory and experiment again in the common, but mistaken, assumption that measures are made and experimentally compared in order to discover scientific laws. History shows that measures are rarely made until the relevant law is effectively embodied in an instrument (Kuhn, 1961/1977, pp. 218-9): “…historically the arrow of causality is largely from the technology to the science” (Price, 1986, p. 240). Instruments do not provide just measures; rather they produce the phenomenon itself in a way that can be controlled, varied, played with, and learned from (Heilbron, 1993, p. 3; Hankins & Silverman, 1999; Rabkin, 1992). The term “technoscience” has emerged as an expression denoting recognition of this priority of the instrument (Baird, 1997; Ihde & Selinger, 2003; Latour, 1987).

Because technology often dictates what, if any, phenomena can be consistently produced, it constrains experimentation and theorizing by focusing attention selectively on reproducible, potentially interpretable effects, even when those effects are not well understood (Ackermann, 1985; Daston & Galison, 1992; Ihde, 1998; Hankins & Silverman, 1999; Maasen & Weingart, 2001). Criteria for theory choice in this context stem from competing explanatory frameworks’ experimental capacities to facilitate instrument improvements, prediction of experimental results, and gains in the efficiency with which a phenomenon is produced.

In this context, the relatively recent introduction of measurement models requiring additive, invariant parameterizations (Rasch, 1960) provokes speculation as to the effect on the human sciences that might be wrought by the widespread availability of consistently reproducible effects expressed in common quantitative languages. Paraphrasing Price’s comment on steam engines and thermodynamics, might it one day be said that as yet unforeseeable advances in reading theory will owe far more to the Lexile analyzer (Stenner, et al., 2006) than ever the Lexile analyzer owed reading theory?

Kuhn (1961/1977) speculated that the second scientific revolution of the early- to mid-nineteenth century followed in large part from the full mathematization of physics, i.e., the emergence of metrology as a professional discipline focused on providing universally accessible, theoretically predictable, and evidence-supported uniform units of measurement (Roche, 1998). Kuhn (1961/1977, p. 220) specifically suggests that a number of vitally important developments converged about 1840 (also see Hacking, 1983, p. 234). This was the year in which the metric system was formally instituted in France after 50 years of development (it had already been obligatory in other nations for 20 years at that point), and metrology emerged as a professional discipline (Alder, 2002, p. 328, 330; Heilbron, 1993, p. 274; Kula, 1986, p. 263). Daston (1992) independently suggests that the concept of objectivity came of age in the period from 1821 to 1856, and gives examples illustrating the way in which the emergence of strong theory, shared metric standards, and experimental data converged in a context of particular social mores to winnow out unsubstantiated and unsupportable ideas and contentions.

Might a similar revolution and new advances in the human sciences follow from the introduction of evidence-based, theoretically predictive, instrumentally mediated, and mathematical uniform measures? We won’t know until we try.

Figure. The Dialectical Interactions and Mutual Mediations of Theory, Data, and Instruments

Figure. The Dialectical Interactions and Mutual Mediations of Theory, Data, and Instruments

Acknowledgment. These ideas have been drawn in part from long consideration of many works in the history and philosophy of science, primarily Ackermann (1985), Ihde (1991), and various works of Martin Heidegger, as well as key works in measurement theory and practice. A few obvious points of departure are listed in the references.

References

Ackermann, J. R. (1985). Data, instruments, and theory: A dialectical approach to understanding science. Princeton, New Jersey: Princeton University Press.

Alder, K. (2002). The measure of all things: The seven-year odyssey and hidden error that transformed the world. New York: The Free Press.

Aldrich, J. (1989). Autonomy. Oxford Economic Papers, 41, 15-34.

Andrich, D. (2004, January). Controversy and the Rasch model: A characteristic of incompatible paradigms? Medical Care, 42(1), I-7–I-16.

Baird, D. (1997, Spring-Summer). Scientific instrument making, epistemology, and the conflict between gift and commodity economics. Techné: Journal of the Society for Philosophy and Technology, 3-4, 25-46. Retrieved 08/28/2009, from http://scholar.lib.vt.edu/ejournals/SPT/v2n3n4/baird.html.

Baird, D. (2002, Winter). Thing knowledge – function and truth. Techné: Journal of the Society for Philosophy and Technology, 6(2). Retrieved 19/08/2003, from http://scholar.lib.vt.edu/ejournals/SPT/v6n2/baird.html.

Burdick, D. S., Stone, M. H., & Stenner, A. J. (2006). The Combined Gas Law and a Rasch Reading Law. Rasch Measurement Transactions, 20(2), 1059-60 [http://www.rasch.org/rmt/rmt202.pdf].

Carroll-Burke, P. (2001). Tools, instruments and engines: Getting a handle on the specificity of engine science. Social Studies of Science, 31(4), 593-625.

Daston, L. (1992). Baconian facts, academic civility, and the prehistory of objectivity. Annals of Scholarship, 8, 337-363. (Rpt. in L. Daston, (Ed.). (1994). Rethinking objectivity (pp. 37-64). Durham, North Carolina: Duke University Press.)

Daston, L., & Galison, P. (1992, Fall). The image of objectivity. Representations, 40, 81-128.

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

Galison, P. (1999). Trading zone: Coordinating action and belief. In M. Biagioli (Ed.), The science studies reader (pp. 137-160). New York, New York: Routledge.

Hacking, I. (1983). Representing and intervening: Introductory topics in the philosophy of natural science. Cambridge: Cambridge University Press.

Hankins, T. L., & Silverman, R. J. (1999). Instruments and the imagination. Princeton, New Jersey: Princeton University Press.

Heelan, P. A. (1983, June). Natural science as a hermeneutic of instrumentation. Philosophy of Science, 50, 181-204.

Heelan, P. A. (1998, June). The scope of hermeneutics in natural science. Studies in History and Philosophy of Science Part A, 29(2), 273-98.

Heidegger, M. (1977). Modern science, metaphysics, and mathematics. In D. F. Krell (Ed.), Basic writings [reprinted from M. Heidegger, What is a thing? South Bend, Regnery, 1967, pp. 66-108] (pp. 243-282). New York: Harper & Row.

Heidegger, M. (1977). The question concerning technology. In D. F. Krell (Ed.), Basic writings (pp. 283-317). New York: Harper & Row.

Heilbron, J. L. (1993). Weighing imponderables and other quantitative science around 1800. Historical studies in the physical and biological sciences), 24(Supplement), Part I, pp. 1-337.

Hessenbruch, A. (2000). Calibration and work in the X-ray economy, 1896-1928. Social Studies of Science, 30(3), 397-420.

Ihde, D. (1983). The historical and ontological priority of technology over science. In D. Ihde, Existential technics (pp. 25-46). Albany, New York: State University of New York Press.

Ihde, D. (1991). Instrumental realism: The interface between philosophy of science and philosophy of technology. (The Indiana Series in the Philosophy of Technology). Bloomington, Indiana: Indiana University Press.

Ihde, D. (1998). Expanding hermeneutics: Visualism in science. Northwestern University Studies in Phenomenology and Existential Philosophy). Evanston, Illinois: Northwestern University Press.

Ihde, D., & Selinger, E. (Eds.). (2003). Chasing technoscience: Matrix for materiality. (Indiana Series in Philosophy of Technology). Bloomington, Indiana: Indiana University Press.

Kuhn, T. S. (1961/1977). The function of measurement in modern physical science. Isis, 52(168), 161-193. (Rpt. In T. S. Kuhn, The essential tension: Selected studies in scientific tradition and change (pp. 178-224). Chicago: University of Chicago Press, 1977).

Kula, W. (1986). Measures and men (R. Screter, Trans.). Princeton, New Jersey: Princeton University Press (Original work published 1970).

Lapre, M. A., & Van Wassenhove, L. N. (2002, October). Learning across lines: The secret to more efficient factories. Harvard Business Review, 80(10), 107-11.

Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York, New York: Cambridge University Press.

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

Lewin, K. (1951). Field theory in social science: Selected theoretical papers (D. Cartwright, Ed.). New York: Harper & Row.

Maas, H. (2001). An instrument can make a science: Jevons’s balancing acts in economics. In M. S. Morgan & J. Klein (Eds.), The age of economic measurement (pp. 277-302). Durham, North Carolina: Duke University Press.

Maasen, S., & Weingart, P. (2001). Metaphors and the dynamics of knowledge. (Vol. 26. Routledge Studies in Social and Political Thought). London: Routledge.

Mendelsohn, E. (1992). The social locus of scientific instruments. In R. Bud & S. E. Cozzens (Eds.), Invisible connections: Instruments, institutions, and science (pp. 5-22). Bellingham, WA: SPIE Optical Engineering Press.

Polanyi, M. (1964/1946). Science, faith and society. Chicago: University of Chicago Press.

Price, D. J. d. S. (1986). Of sealing wax and string. In Little Science, Big Science–and Beyond (pp. 237-253). New York, New York: Columbia University Press.

Rabkin, Y. M. (1992). Rediscovering the instrument: Research, industry, and education. In R. Bud & S. E. Cozzens (Eds.), Invisible connections: Instruments, institutions, and science (pp. 57-82). Bellingham, Washington: SPIE Optical Engineering Press.

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

Roche, J. (1998). The mathematics of measurement: A critical history. London: The Athlone Press.

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.

Stenner, A. J., Burdick, H., Sanford, E. E., & Burdick, D. S. (2006). How accurate are Lexile text measures? Journal of Applied Measurement, 7(3), 307-22.

Thurstone, L. L. (1959). The measurement of values. Chicago: University of Chicago Press, Midway Reprint Series.

Wright, B. D. (1997, Winter). A history of social science measurement. Educational Measurement: Issues and Practice, 16(4), 33-45, 52 [http://www.rasch.org/memo62.htm].

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

Al Gore: Marshalling the Collective Will is NOT the Problem–The Problem is the Problem!

November 22, 2009

In his new book, former vice-president Al Gore says we have in hand all the tools we need to solve the climate change crises, except the collective will to do anything about them. I respectfully beg to differ. Finding the will is not the problem. We already have it and we have it volumes sufficient to the task. Gore is also wrong in claiming we have the tools we need. There are entire classes of scientific and economic tools that we are missing. It is because we lack the right tools that we are unable to focus and channel our will for solutions.

The short version of my argument is that we don’t have scientific, universally uniform, and ubiquitously used metrics for measuring overall environmental quality. Because we don’t have the measures, we can’t and don’t effectively and efficiently manage our natural capital and environmental assets. Without metrics akin to barrels of oil or bushels of grain, we don’t have markets for matching environmental quality supply with demand for it.

Without tools as essential as metrics and markets, we can’t harness our existing will to improve our relationship with the earth. What will do we have, you might ask? Our collective will is expressed in the profit motive. What we need to do is set up metrics and markets to harness the energy of the profit motive. We need to create systems for trading natural capital (and human and social capital) so that we generate real wealth and drive happiness indexes north by realizing human potential, building thriving communities, and nurturing sustainable environments. The profit motive is not our enemy. It is the source of energy we need to deal with the multiple crises we face: human, social, and environmental.

Now for the long version of my argument. The problem is the problem. We restrict our options for solving problems by the way we frame the issue. Einstein supposedly pointed out that big problems, ones framed at a level where they define the entire paradigmatic orientation to a class of smaller, solvable problems, cannot be solved from within the paradigm they emerge from. We tend to define problems from the modern point of view, in a Cartesian fashion, from the point of view of a subject that is separate from, and in no way involved in the construction of, the objects it encounters. What I want to point out is that it is this Cartesian orientation to problem definition that is itself the problem!

Set aside your opinions on the basic issues concerning climate change, and think about what’s going on. It is undeniable that human activities are implicated in changes to the environment, and that we have to learn to manage our effects on the planet, or they will feed back on us in potentially harmful ways. This is the nature of life in the flux and flow of ecological relationships. It is one of many ways in which observers are inherently implicated in constructing what is observed, which is recognized as holding true as much in physics as in anthropology. These are uncontroversial facts, quite apart from any concern with climate change.

And what these feedback loops imply, as has indeed already been pointed out by generations of scholars and thinkers, is that there is no such thing as a pure Cartesian subject separate from its objects. We shape the things in our world, and those things, in turn, shape us. Subjects and objects are mutually implicated. All observers are participant observers. It is inevitable that what we do and think will change the world, and the new world will require us to think and act differently.

The plethora of environmental crises we face are therefore situated in a new non-Cartesian paradigm. It is a fundamental error of the first order to approach a non-Cartesian problem as though it were merely another variation on the usual kind of thing that can be addressed fairly well from the Cartesian dualist perspective. When we think, as Al Gore does, that we should be socialistically organizing resources for a centrally-organized 5-year plan of attack on environmental problems, we are missing the point.

This approach can be put to work only in terms of an authoritarian form of control directed by a dictatorial panel of experts, a military junta, or a self-appointed czar. Framed from a Cartesian point of view, no democratic process will ever compel voters to do what needs to be done. As was illustrated so dramatically by the fall of Communism, the socialistic manipulation of the concrete particulars of human, social, and environmental problems is unsustainable and socially irresponsible.

The fact is that non-Cartesian problems are only made worse when we try to solve them with Cartesian solutions. This is why non-Cartesian problems are often described by philosophers as “hermeneutic,” a word that derives from the name of the Greek god Hermes, known by the ancient Romans as Mercury. Like liquid mercury, non-Cartesian problems merely split and multiply when we grasp at them clumsily ignoring our own involvement in the creation of the problem.

So we can go on trying to herd cats or nail jello to the wall, but to be part of the solution and not just another way of being part of the problem, we need to set up systems of thought and behavior that are not internally inconsistent and self-contradictory. No matter what we do, if we keep on marshalling resources to attack problems in deliberate and systematic ignorance of this cross-paradigmatic dissonance, we can only make matters worse.

What else can be done? Just what does it mean to go with the flow of the mutual implication of subject and object? How can we explicitly model the problem to include the participant observer?

“The medium is the message,” to quote Marshall McLuhan. As was pointed out so humorously by Woody Allen in his film, “Annie Hall,” this expression is often repeated and often misunderstood. Though all can see that the news and entertainment media are ubiquitous, the meaning of our captivation with the media of creative expression has not yet been clarified sufficiently well for generalized understanding.

Significant advances have occurred in recent years, however. The media we are captivated by define and limit not only how and what we communicate, but who and what we have been, are, and could be. Depending on the quality of their transparency and of the biases that color them, media convey moral, human, and economic values of various kinds. The media through which we express values include every conceivable technology, from alphabets and phonemes to buildings, clothing, and food preparation, to musical instruments, and the creations of art and science.

Media are at the crux of the lesson we have to learn if we are to frame the problems of environmental management so that we are living solutions, not exacerbating problems. Media of all kinds, from pen and paper to television to the Internet, are fundamentally technical. In fact, media are the original technologies. The words “text,” “textile,” and “technique” all derive from the Greek “techne,” to make, and have even deeper roots in the Sanskrit “TEK.” Technology is our primary medium of shared meaning. Technology embodies the meanings we create and distributes their values across society and around the world.

What we need to do to effect non-Cartesian solutions then is to dwell deeply with our shared meanings and values, and find new ways of living them out, ways that embody the unity of subject and object, problem and solution. Nice rhetoric, you might say, but what does it mean? What is its practical consequence?

Put in academic terms, the pragmatic issue concerns the nature of technology and how it provides measures of reality serving as the media through which we experience the world in terms of shared universals. Primary sources here include the works of writers like Latour, Wise, Jasanoff, Knorr-Cetina, Schaffer, Ihde, Heidegger, and others cited in previous posts in this blog, and in my published work.

To do more to cut to the chase, we can start to think of language and technology as embodying problem-solution unities. Words and tools are situated within ecologies of relationships that define their meanings and functions. We need to be more sensitive to the way meanings and values become embodied in language and technologies, and then are distributed across far-flung networks to coordinate collectively harmonized thought and action.

To get right down to where this all is leading, though it is probably far from obvious, the appropriate non-Cartesian orientation to the problems of environmental management raised in Al Gore’s new book ultimately culminates in creation of the technical networks through which we distribute measures of what we want to manage. These networks comprise the ecologies of meaning and values that we inhabit. Not coincidentally, they also create the markets in which human, social, and natural capital can be efficiently and effectively traded.

When these networks and markets are created, finding the collective will to deal with the environmental challenges we face will be the least of our problems. The profit motive is an exceptionally strong force. What we ought to be doing is figuring out how to harness it as the engine of social change. This contrasts diametrically with Al Gore’s perspective, which treats the profit motive as part of the problem.

Technical networks of instruments traceable to reference standards, and markets for the exchange of the values measured by those instruments, are what we ought to be focusing on. The previous post in this blog proposes an Intangible Assets Metric System, and is related to earlier posts on the role of common currencies for the exchange of meaningful quantitative values in creating functional markets for human, social, and natural capital. What we need are these infrastructural supports for creating the efficient markets in which demand for environmental solutions can be matched the supply of those solutions. The failure of socialism is testimony to the futility of trying to man-handle our way forward by brute force.

Of course, I will continue living out my life’s mission and passion by continuing to elaborate variations, explanations, and demonstrations of how this could be so….

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