Archive for the ‘Interests’ 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


Fisher, W. P., Jr. (2010, June 13-16). Rasch, Maxwell’s method of analogy, and the Chicago tradition. In G. Cooper (Chair), Https:// 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),

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.

Review of “Advancing Social Impact Investments Through Measurement”

August 24, 2012

Over the last few days, I have been reading several of the most recent issues of the Community Development Investment Review, especially volume 7, number 2, edited by David Erickson of the Federal Reserve Bank of San Francisco, reporting the proceedings of the March 21, 2011 conference in Washington, DC on advancing social impact investments through measurement. I am so excited to see this work that I am (truly) fairly trembling with excitement. I feel as though I’ve finally made my way home. There are so many points of contact, it’s hard to know where to start. After several days of concentrated deep breathing and close study of the CDIR, it’s now possible to formulate some coherent thoughts to share.

The CDIR papers start to sort out the complex issues involved in clarifying how measurement might contribute to the integration of impact investing and community development finance. I am heartened by the statement that “The goal of the Review is to bridge the gap between theory and practice and to enlist as many viewpoints as possible—government, nonprofits, financial institutions, and beneficiaries.” On the other hand, the omission of measurement scientists from that list of viewpoints adds another question to my long list of questions as to why measurement science is so routinely ignored by the very people who proclaim its importance. The situation is quite analogous to demanding more frequent conversational interactions from colleagues while ignoring the invention of the telephone and not providing them with the tools and network connections.

The aims shared by the CDIR contributors and myself are evident in the fact that David Erickson opens his summary of the March 21, 2011 conference with the same quote from Robert Kennedy that I placed at the end of my 2009 article in Measurement (see references below; all papers referenced are available by request if they are not already online). In that 2009 paper, in others I’ve published over the last several years, in presentations I’ve made to my measurement colleagues abroad and at home, and in various entries in my blog, I take up virtually all of the major themes that arose in the DC conference: how better measurement can attract capital to needed areas, how the cost of measurement repels many investors, how government can help by means of standard setting and regulation, how diverse and ambiguous investor and stakeholder interests can be reconciled and/or clarified, etc.

The difference, of course, is that I present these issues from the technical perspective of measurement and cannot speak authoritatively or specifically from the perspectives represented by the community development finance and impact investing fields. The bottom line take-away message for these fields from my perspective is this: unexamined assumptions may unnecessarily restrict assessments of problems and their potential solutions. As Salamon put it in his remarks in the CDIR proceedings from the Washington meeting (p. 43), “uncoordinated innovation not guided by a clear strategic concept can do more than lose its way: it can do actual harm.”

A clear strategic concept capable of coordinating innovations in social impact measurement is readily available. Multiple, highly valuable, and eminently practical measurement technologies have proven themselves in real world applications over the last 50 years. These technologies are well documented in the educational, psychological, sociological, and health care research literatures, as well as in the practical experience of high stakes testing for professional licensure and certification, for graduation, and for admissions.

Numerous reports show how to approach problems of quantification and standards with new degrees of rigor, transparency, meaningfulness, and flexibility. When measurement problems are not defined in terms of these technologies, solutions that may offer highly advantageous features are not considered. When the area of application is as far reaching and fundamental as social impact measurement, not taking new technologies into account is nothing short of tragic. I describe some of the new opportunities for you in a Technical Postscript, below.

In his Foreword to the CDIR proceedings issue, John Moon mentions having been at the 2009 SoCap event bringing together stakeholders from across the various social capital markets arenas. I was at the 2008 SoCap, and I came away from it with much the same impression as Moon, feeling that the palpable excitement in the air was more than tempered by the evident fact that people were often speaking at cross purposes, and that there did not seem to be a common object to the conversation. Moon, Erickson, and their colleagues have been in one position to sort out the issues involved, and I have been in another, but we are plainly on converging courses.

Though the science is in place and has been for decades, it will not and cannot amount to anything until the people who can best make use of it do so. The community development finance and impact investing fields are those people. Anyone interested in getting together for an informal conversation on topics of mutual interest should feel free to contact me.

Technical Postscript

There are at least six areas in efforts to advance social impact investments via measurement that will be most affected by contemporary methods. The first has to do with scale quality. I won’t go into the technical details, but numbers do not automatically stand for something that adds up the way they do. Mapping a substantive construct onto a number line requires specific technical expertise; there is no evidence of that expertise in any of the literature I’ve seen on social impact investing, or on measuring intangible assets. This is not an arbitrary bit of philosophical esoterica or technical nicety. This is one of those areas where the practical value of scientific rigor and precision comes into its own. It makes all the difference in being able to realize goals for measurement, investment, and redefining profit in terms of social impacts.

A second area in which thinking on social impact measurement will be profoundly altered by current scaling methods concerns the capacity to reduce data volume with no loss of information. In current systems, each indicator has its own separate metric. Data volume quickly multiplies when tracking separate organizations for each of several time periods in various locales. Given sufficient adherence to data quality and meaningfulness requirements, today’s scaling methods allow these indicators to be combined into a single composite measure—from which each individual observation can be inferred.

Elaborating this second point a bit further, I noted that some speakers at the 2011 conference in Washington thought reducing data volume is a matter of limiting the number of indicators that are tracked. This strategy is self-defeating, however, as having fewer independent observations increases uncertainty and risk. It would be far better to set up systems in which the metrics are designed so as to incorporate the amount of uncertainty that can be tolerated in any given decision support application.

The third area I have in mind deals with the diverse spectrum of varying interests and preferences brought to the table by investors, beneficiaries, and other stakeholders. Contemporary approaches in measurement make it possible to adapt the content of the particular indicators (counts or frequencies of events, or responses to survey questions or test items) to the needs of the user, without compromising the comparability of the resulting quantitative measure. This feature makes it possible to mass customize the content of the metrics employed depending on the substantive nature of the needs at that time and place.

Fourth, it is well known that different people judging performances or assigning numbers to observations bring different personal standards to bear as they make their ratings. Contemporary measurement methods enable the evaluation and scaling of raters and judges relative to one another, when data are gathered in a manner facilitating such comparisons. The end result is a basis for fair comparisons, instead of scores that vary depending more on which rater is observing than on the quality of the performance.

Fifth, much of the discussion at the conference in Washington last year emphasized the need for shared data formatting and reporting standards. As might be guessed from the prior four areas I’ve described, significant advances have occurred in standard setting methods. It is suggested in the CDIR proceedings that the Treasury Department should be the home to a new institute for social impact measurement standards. In a series of publications over the last few years, I have suggested a need for an Intangible Assets Metric System to NIST and NSF (see below for references and links; all papers are available on request). That suggestion comes up again in my third-prize winning entry in the 2011 World Standards Day paper competition, sponsored by NIST and SES (the Society for Standards Professionals), entitled “What the World Needs Now: A Bold Plan for New Standards.” (See below for link.)

Sixth, as noted by Salamon (p. 43), “metrics are not neutral. They not only measure impact, they can also shape it.” Though this is not likely exactly what Salamon meant, one of the most exciting areas in measurement applications in education in recent years, one led in many ways by my colleague, Mark Wilson, and his group at UC Berkeley, concerns exactly this feedback loop between measurement and impact. In education, it has become apparent that test scaling reveals the order in which lessons are learned. Difficult problems that require mastery of easier problems are necessarily answered correctly less often than the easier problems. When the difficulty order of test questions in a given subject remains constant over time and across thousands of students, one may infer that the scale reveals the path of least resistance. Individualizing instruction by targeting lessons at the student’s measure has given rise to a concept of formative assessment, distinct from the summative assessment of accountability applications. I suspect this kind of a distinction may also prove of value in social impact applications.

Relevant Publications and Presentations

Fisher, W. P., Jr. (2002, Spring). “The Mystery of Capital” and the human sciences. Rasch Measurement Transactions, 15(4), 854 [].

Fisher, W. P., Jr. (2004, Thursday, January 22). Bringing capital to life via measurement: A contribution to the new economics. In  R. Smith (Chair), Session 3.3B. Rasch Models in Economics and Marketing. Second International Conference on Measurement in Health, Education, Psychology, and Marketing: Developments with Rasch Models, The International Laboratory for Measurement in the Social Sciences, School of Education, Murdoch University, Perth, Western Australia.

Fisher, W. P., Jr. (2005, August 1-3). Data standards for living human, social, and natural capital. In Session G: Concluding Discussion, Future Plans, Policy, etc. Conference on Entrepreneurship and Human Rights [], Pope Auditorium, Lowenstein Bldg, Fordham University.

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [].

Fisher, W. P., Jr. (2008, 3-5 September). New metrological horizons: Invariant reference standards for instruments measuring human, social, and natural capital. Presented at the 12th International Measurement Confederation (IMEKO) TC1-TC7 Joint Symposium on Man, Science, and Measurement, Annecy, France: University of Savoie.

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

Fisher, W. P.. Jr. (2009). NIST Critical national need idea White Paper: Metrological infrastructure for human, social, and natural capital (Tech. Rep., Washington, DC: National Institute for Standards and Technology.

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),

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

Fisher, W. P., Jr. (2011). Measuring genuine progress by scaling economic indicators to think global & act local: An example from the UN Millennium Development Goals project. Retrieved 18 January 2011, from Social Science Research Network:

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, May/June). What the world needs now: A bold plan for new standards. Standards Engineering, 64(3), 1 & 3-5 [].

Fisher, W. P., Jr., & Stenner, A. J. (2011, January). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation:

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium,, Jena, Germany.

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On Leaping to Conclusions: Learning Through Prejudices and Evaluating Them

December 22, 2009

Back at Marianjoy Rehab Hospital in the late 1980s and early 1990s, Richard F. Harvey, MD, the Medical Director, had a sign in his office that’s always stuck in my mind. It had an image of a kangaroo on it, with the words “Some people get their exercise by leaping to conclusions.”

Yes, I am as guilty as anyone of that. And I’m particularly sensitive to the issue because my work involves a lot of thinking and research into how we all inevitably learn through what we already know. We develop physically, cognitively, and morally by filtering incoming data through the screen of what we already are, what we’ve already experienced and learned. As we integrate physical sensations and learn to coordinate our limbs and hands with our eyes, we move from babyhood to childhood. As we learn how to pronounce words and construct sentences, we learn to speak. With the basics of communication in hand, we pick up the alphabet, spelling, grammar, and composition in the course of learning to read and write. Then we use what we’ve read and experienced to think through what is and what ought to be as we try to build a better world.

But we often leap to conclusions when we hear, see, or read something that doesn’t quite make sense to us. I’m becoming increasingly attuned and sensitive to the ways in which I, and others, do this. It happens subtly sometimes, when perhaps we’ve encountered something we don’t really know much about, but which seems obviously wrong for some reason. It is basically an issue of prejudice, but not in the big sense of the word. I’m thinking of the little ways in which we filter experience, in which attention is directed to what we find especially meaningful, and in which matters presumed to be of peripheral concern are pushed to the margins. We must inevitably do these kinds of things; if we didn’t, we’d be overwhelmed with uninterpretable data.

The philosophical issues involved have been an explicit focus of interpretation theory (hermeneutics) for over a century, with roots dating to ancient Greece. Changes in the perception of prejudice as the necessary door through which all new experience and knowledge is processed have led to thorough reconsiderations of what it is and what its place in clear thinking might be. In his landmark work on the creation of meaning in interpretation, Gadamer (1989, p. 490), for instance, remarks that “there is undoubtedly no understanding that is free of all prejudices, however much the will of our knowledge must be directed toward escaping their thrall.”

It happens that some fields of research make investigators more aware of the need to pay attention to prejudices and presuppositions than others. In the preface (pp. xi-xiii) to his classic 1977 book, The Essential Tension, Thomas Kuhn recounts an experience from the summer of 1947 that led to his appreciation for an explicit theory of interpretation. He had been completely perplexed by Aristotle’s account of motion, in which Aristotle writes a great many things that appear blatantly absurd. Kuhn was very puzzled and disturbed by this, as Aristotle made many astute observations in other areas, such as biology and political behavior. He eventually came to see what Aristotle was in fact talking about, and he then came to routinely offer the following maxim to his students:

“When reading the works of an important thinker [or anyone else who usually seems to have a modicum of coherence], look first for the apparent absurdities in the text and ask yourself how a sensible person could have written them. When you find an answer, I continue, when those passages make sense, then you may find that more central passages, ones you previously thought you understood, have changed their meaning.”

As Kuhn goes on to say, if his book was addressed primarily to historians, this point wouldn’t be worth making, as historians are in the business of precisely this kind of interpretive back-and-forth, as are many philosophers, literary critics, writers, social scientists, educators, and artists. But as a physicist, Kuhn says that the discovery of hermeneutics not only made history seem consequential, it changed his view of science. As is well known, his skill in practicing hermeneutics changed a great many people’s views of science.

In my personal experience, however, one does not need to be a physicist to be guilty of dismissing apparent absurdities. In a classic article, Paul Ricoeur (1974) refers to uncontrolled submission to prejudices as “the violence of the premature conclusion.” He (Ricoeur, 1974, p. 96) agrees with Gadamer about the inevitability of prejudice at some level, saying, “There can be no philosophy without presuppositions.”

And agreement with this general attitude is shared even by someone as apparently unlikely as Jacques Derrida, reviled by some (for instance, Bloom, 1987, p. 387, among many others) for appearing to hold that reason is futile, precisely because it is inevitably tied to the interests that shape our presuppositions. Derrida was perplexed by these reactions to his work, strenuously objecting and pointing out that

“…people who read me and think I’m playing with or transgressing norms–which I do, of course–usually don’t know what I know: that all of this has not only been made possible by but is constantly in contact with very classical, rigorous, demanding discipline in writing, in ‘demonstrating,’ in rhetoric. …the fact that I’ve been trained in and that I am at some level true to this classical teaching is essential. … When I take liberties, it’s always by measuring the distance from the standards I know or that I’ve been rigorously trained in” (Derrida, 2003, pp. 62-63).

Contrary to what many of his readers presume, Derrida considered himself true to philosophy (1989b, p. 218), agreeing that mathematically ideal objects are the “absolute model for any object whatsoever” (1989a, p. 66), and that metaphysical presuppositions are unavoidable (Derrida, 1978, pp. 280-281). What we have in this extreme case, then, is an ironic example of becoming subject to prejudices concerning the role of those prejudices in shaping understanding. Bloom (1987), for his part, is also tragically ironic in taking deconstruction to be a closing of the American mind when it actually represents ways of opening further than ever before, as but one moment in cycling through the ontological method (Heidegger, 1982, pp. 19-23, 320-330; Fisher, 2010) from (1) reducing experience to words to (2) applying what has been said in practice to (3) creatively destroying our routines to uncover hidden prejudices via deconstruction, which then informs a return to new reductions.

What happened in Derrida’s case gives a good context for considering the smaller everyday ways in which we counter-productively dismiss apparent nonsense, commit small acts of violence against others and ourselves, and fail to appreciate as well as we could the opportunities with which we are presented. There seem to be a lot of ways in which we build up a righteous sense of ourselves over against the madness of the world by projecting inanities on others instead of asking, as Kuhn found he had to ask, how a reasonable person could arrive at such a position.

Of course, it is simply easier to assume other people are not reasonable, or that their methods of reasoning are insufficient, unnecessary, or both. And, of course, it takes a lot of time to try to understand how others might be reasonable in ways that we have not conceived. Anyone who has experienced close but difficult relationships with others knows how much effort can be expended in achieving even small gains in mutual understanding.

So is there really very little or nothing that can be done to find other ways besides leaping to conclusions to get our exercise? We need something more than patience and tolerance, valuable though these are over the long term for allowing new learning to unfold in its own time. But simply allowing others the method of their madness does nothing to advance the general state of things, when we have so many pressing demands to learn from each other.

What we really need is a science that systematically tests our preconceptions and checks them for internal consistency and productive potential, via the checks and balances of mutually mediated theory, data, and instruments (Ackermann, 1985;  Ihde, 1991). In our specialized world, we wind up living in closed micro-societies with others of like mind who do little to challenge the boundaries of new thinking. Though old ethnic prejudices persist to the point of tribal wars in many parts of the world, they are more subtle today those of the past in other places. For instance, in the United States, Poles, Italians, and Irish previously found each other mutually distasteful, and despite ongoing institutional racism, Barack Obama symbolizes a significant shift in focus.

A broader concern with prejudice in general would be an example of the tide that lifts all boats. No one is exempted from culpability, and everyone would benefit from the removal of their own and others’ blinders. Many significant obstacles to social progress are based in unexamined prejudices.

  • Is the conduct of business inherently immoral? Many academics seem to think so, though they themselves participate in the larger economy, though no one has ever proposed a better way of improving the overall quality of life for society at large, and though universities, too, are driven by profits of various kinds.
  • Are soldiers inherently immoral? Though killing is absolutely immoral, and the training of young people to kill and to be insensitive to killing is abhorrent, would it be better to allow malicious evil to run rampant? If not, should we not do a better job of honoring and respecting those willing to give their lives? More fundamentally, are we ever going to own up as a society to the trade-offs in the calculus of lives saved vs those sacrificed? If not, how will we ever effectively oppose unjust wars or unsafe consumer products?
  • Is government inherently obstructionist and wasteful? Or does society require that its will be embodied in independent representation and balanced legislative, judicial, and executive powers? Is not the optimal role of government found in providing the infrastructural media for the fair and just expression of the collective social will? If we want to restrict the role of government in our lives, should we not then be investing our resources in uniform metrics for the efficient and effective management of human, social, and natural capital so that we can take control of education, health care, social services, and environmental quality directly?
  • Does the market need to be controlled by external mechanisms? Few would say any longer that it always knows best, though the extent that its behavior is a function of the information available is still unknown. Could the available information be improved in significant ways, perhaps by creating the highest possible quality information for each significant form of capital?
  • Is science an inherent good? Can we somehow slow or stop it, or, like democracy, can we improve it only by applying it to itself?
  • Is the measurement of human qualities inherently reductionistic, always and everywhere an immoral and meaningless categorization? Is psychosocial measurement mathematically equivalent with physical measurement in quality and in its potential for fostering scientific, humanistic, and economic revolutions impossible? Or might it already be in hand, and only our prejudices are preventing us from seeing it and using it?
  • Is addressing environmental concerns completely at odds with business interests, or are there in fact many business people who recognize that long-term profitability requires close attention to sustainability?
  • Are academics who focus on class oppression, sexism, racism, and the constant play of power as expressions of vested interests necessarily always wrong?
  • Instead of dismissing the excesses of the consumer culture as inherently devoid of any redeeming value, what is the message we need to learn that is being conveyed in this medium?
  • Are unreligious people automatically going to hell? Are those who believe their way is the only way automatically going to heaven? Is it possible to find and build on the elements of forgiveness and redemption found in all religions?

How might we find the germ of truth that gives life to each perspective? How might we reconcile and heal our own internal differences so that we can do more to accept the differences between us, and build on them in ways that brings out the real value of e pluribus unum, “out of many one”?

Far from being locked by these questions into a permanent analysis paralysis, there are concrete things that can be done to examine, test, and overcome our prejudices. I’m looking forward to engaging in this work with any and all willing to take it on. There just has to be a better way for us to get our exercise!


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

Bloom, A. (1987). The closing of the American mind: How higher education has failed democracy and impoverished the souls of today’s students. New York: Simon & Schuster.

Derrida, J. (1978). Structure, sign and play in the discourse of the human sciences. In Writing and difference (pp. 278-93). Chicago: University of Chicago Press.

Derrida, J. (1989a). Edmund Husserl’s Origin of Geometry: An introduction. Lincoln: University of Nebraska Press.

Derrida, J. (1989b). On colleges and philosophy: An interview conducted by Geoffrey Bennington. In L. Appignanesi (Ed.), Postmodernism: ICA documents (pp. 209-28). London, England: Free Association Books.

Derrida, J. (2003). Interview on writing. In G. A. Olson & L. Worsham (Eds.), Critical intellectuals on writing (pp. 61-9). Albany, New York: State University of New York Press.

Fisher, W. P., Jr. (2010). Reducible or irreducible? Mathematical reasoning and the ontological method. Journal of Applied Measurement, p. in press.

Gadamer, H.-G. (1989). Truth and method (J. Weinsheimer & D. G. Marshall, Trans.) (Rev. ed.). New York: Crossroad (Original work published 1960).

Heidegger, M. (1982). The basic problems of phenomenology (J. M. Edie, Ed.) (A. Hofstadter, Trans.). Studies in Phenomenology and Existential Philosophy. Bloomington, Indiana: Indiana University Press (Original work published 1975).

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.

Kuhn, T. S. (1977). The essential tension: Selected studies in scientific tradition and change. Chicago, Illinois: University of Chicago Press.

Ricoeur, P. (1974). Violence and language. In D. Stewart & J. Bien (Eds.), Political and social essays by Paul Ricoeur (pp. 88-101). Athens, Ohio: Ohio University Press.

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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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