Archive for the ‘metrology’ Category

Comment on Kerrey and Leeds in WSJ

November 20, 2013

Writing in today’s Wall Street Journal, Bob Kerrey and Jeffery T. Leeds note the unintended consequences likely to follow from new higher education regulations proposed by the U.S. Department of Education. Cutting to the chase, Kerrey and Leeds’ key points (emphases added) are that:

  • “Absent innovative, competitive—and, yes, disruptive—pressure to raise quality and lower costs, all the well-intentioned federal regulation in the world will not make college more accessible.”
  • “He [Secretary of Education, Arne Duncan] should insist on real and significant disclosure. Colleges should be required to post their graduation rates, job-placement rates, the average debt of their students upon graduation, their tax status and any and all information that will enable Americans to make informed decisions when choosing a school.”
  • “The department should also work with schools and colleges to address the fundamental causes of rising tuition, and hold schools accountable for student outcomes instead of their debt.”

These are, of course, exactly the themes repeatedly raised in this blog. Measurement quality is unavoidably implicated in holding schools accountable for student outcomes, in enabling consumers to make informed purchasing decisions, and in raising quality and lowering costs.

To meet the challenges we face, measurement quality must be far more than just a matter of precision and rigor. Quality must also speak to relevance, efficiency, and meaningfulness. Recent history has brought home the lesson that annual tests used solely for accountability purposes will not enable rebalanced quality/cost equations, informed consumer decisions, or fair accountability results. But how might these disparate purposes be efficiently and meaningfully realized?

It is essential that, if teachers are to be responsible for student outcomes and for raising the overall quality of education, formative measuring tools must provide the qualitative and quantitative information they need to be able to act responsibly. The irony is, of course, that the way to overcome the problems of a purely summative focus for educational measurement is to measure more! Now, measuring more need not involve devoting more time exclusively to taking tests. Instead, computerized and online assessments are increasingly integrated into instruction so that measures are made in the course of studying (Cheng and Mok, 2007; Wilson, 2004). Measures are thereby continuously updated, and are plotted in growth charts relative to long range outcome goals.

Furthermore, the qualitative information provided by the measurement process is used to inform teachers and students about what comes next in the individualized curriculum, as well as about special strengths and weaknesses. This information has been shown to be unparalleled in its value for advancing learning in the classroom (Black and Wiliam, 1998, 2009; Hattie, 2008).

But formative assessment alone will not be sufficient to the larger tasks of raising quality and lowering costs. For that, systematic quality improvement methods in schools will need to be joined with comparable outcome measures parents and students can use to inform school choice decisions (Fisher, 2013; Lunenberg, 2010).

Kerrey and Leeds rightly seek an infrastructure capable of disruptive effects, of transforming the inflationary economy of education (and health care). To state again a recurring theme in this blog, the command and control hierarchies of regulatory systems can and should be replaced with a metrological infrastructure of common metrics with the scientific, legal, and financial status of common currencies for the exchange of value. Only when such currencies are in place will we be able to set out clear paths for the informed decisions, improved quality, lower costs, and accountability for outcomes that we seek.

References

Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education, 5(1), 7-74.

Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21, 5-31.

Cheng, Y. C., & Mok, M. M. C. (2007). School-based management and paradigm shift in education: An empirical study. International Journal of Educational Management, 21(6), 517-542.

Fisher, W. P., Jr. (2013). Imagining education tailored to assessment as, for, and of learning: Theory, standards, and quality improvement. Assessment and Learning, 2, in press.

Hattie, J. (2008). Visible learning. New York: Routledge.

Lunenberg, F. C. (2010). Total Quality Management applied to schools. Schooling, 1(1), 1-6.

Wilson, M. (Ed.). (2004). Towards coherence between classroom assessment and accountability. (Vol. 103, Part II, National Society for the Study of Education Yearbooks). Chicago, Illinois: University of Chicago Press.

On the IMEKO 2013 Joint Symposium in Genoa, Italy

November 19, 2013

The most recent instance of the IMEKO (International Measurement Confederation) joint symposium (which now also includes TC-13, the technical committee on measurements in biology and health care, along with TC-1 on Measurement Science and TC-7 on Metrology Education) was held in Genoa, Italy, September 4-6, 2013. The papers presented are available in volume 459 of the Journal of Physics Conference Series at http://iopscience.iop.org/1742-6596/459/ .

Mari and Wilson’s keynote providing a “gentle introduction to Rasch measurement models for metrologists” will be of special interest. Additional Rasch-oriented presentations were made by Maul, Torres-Irribarra, and Wilson; Camargo and Henson; Bezruczko; Stenner; Massof; Stephanou, Pendrill; and Fisher. Readers may also be interested in related work presented by Benoit, Crenna, Rossi, Granovskii, Pavese, Ruhm, Thomas, and others.

An exciting new dialogue between the natural and social sciences is underway. Each has much to learn from the other. Metrology has had little need to attend to the individual-level stochastic processes structuring invariant cognitive and behavioral constructs, and measurement practice in psychology and the social sciences has everything to learn about the value of local traceability to globally uniform units. Everyone interested in contributing to or learning from this dialogue is invited to make their voices heard.

A photo of a majority of the Genoa symposium attendees is available at http://spectronet.de/de/vortraege_bilder/vortraege_2013/15th-joint-international-imeko-tc1tc7tc13-symposiu_hlms3467.html.

A number of presentations involving Rasch measurement models, methods, and results were made at previous IMEKO symposia in Annecy (France), Lisbon (Portugal), London (England), and Jena (Germany) in 2008, 2009, 2010, and 2011, respectively (Fisher, 2009, 2010, 2011). A paper based on Mark Wilson’s keynote address at the 2011 meeting has recently been published in the IMEKO journal, Measurement (Wilson, 2013).

This journal also has a forthcoming celebration of the work of the late Ludwik Finkelstein in press (volume 46, number 8, pp. 2885-2992). Finkelstein made a large number of foundational contributions to educational and conceptual issues in measurement science, and had a special interest in exploring the possibility of a unified science of measurement applicable across the natural and social sciences (see, for instance, Finkelstein, 2003, 2009, 2010).

Wilson’s keynote at the Jena IMEKO symposium in 2011 was given at the invitation of Luca Mari, an engineer and philosopher of measurement based at the Universite Cattaneo, in Castellanza, Italy. Wilson reciprocated the invitation by bringing Mari to last summer’s International Meeting of the Psychometric Society in Lincoln, Nebraska. Mari gave a well-attended workshop on metrology, and an invited address.

Mari is also be a visiting scholar in the Graduate School of Education at the University of California, Berkeley, 18-22 November, 2013. In addition to his contributions to the International Electrotechnical Vocabulary (IEV), Mari is intensely involved in the ongoing revisions to the International Vocabulary of Metrology (known as the VIM; Joint Committee on Guides in Metrology, 2008), especially as this involves efforts continuing Finkelstein’s interest in integrating measurement concepts from all fields into a common frame of reference.

References

Finkelstein, L. (2003). Widely, strongly and weakly defined measurement. Measurement, 34(1), 39-48(10).

Finkelstein, L. (2009). Widely-defined measurement—An analysis of challenges. Measurement, 42(9), 1270-1277.

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

Fisher, W. P., Jr. (2008). Notes on IMEKO symposium. Rasch Measurement Transactions, 22(1), 1147 [http://www.rasch.org/rmt/rmt221.pdf].

Fisher, W. P., Jr. (2010). Unifying the language of measurement. Rasch Measurement Transactions, 24(2), 1278-1281  [http://www.rasch.org/rmt/rmt242.pdf].

Fisher, W. P., Jr. (2012). 2011 IMEKO conference proceedings available online. Rasch Measurement Transactions, 25(4), 1349 [http://www.rasch.org/rmt/rmt254.pdf].

Joint Committee for Guides in Metrology (JCGM/WG 2). (2008). International vocabulary of metrology: Basic and general concepts and associated terms, 3rd ed. Sevres, France: International Bureau of Weights and Measures–BIPM. http://www.bipm.org/utils/common/documents/jcgm/JCGM_200_2008.pdf. Accessed 17 October 2013.

Wilson, M. (2013). Using the concept of a measurement system to characterize measurement models used in psychometrics. Measurement, 46, 3766-3774.

Dispelling Myths about Measurement in Psychology and the Social Sciences

August 27, 2013

Seven common assumptions about measurement and method in psychology and the social sciences stand as inconsistent anomalies in the experience of those who have taken the trouble to challenge them. As evidence, theory, and instrumentation accumulate, will we see a revolutionary break and disruptive change across multiple social and economic levels and areas as a result? Will there be a slower, more gradual transition to a new paradigm? Or will the status quo simply roll on, oblivious to the potential for new questions and new directions? We shall see.

1. Myth: Qualitative data and methods cannot really be integrated with quantitative data and methods because of opposing philosophical assumptions.

Fact: Qualitative methods incorporate a critique of quantitative methods that leads to a more scientific theory and practice of measurement.

2. Myth: Statistics is the logic of measurement.

Fact: Statistics did not emerge as a discipline until the 19th century, while measurement, of course, has been around for millennia. Measurement is modeled at the individual level within a single variable whereas statistics model at the population level between variables. Data are fit to prescriptive measurement models using the Garbage-In, Garbage-Out (GIGO) Principle, while descriptive statistical models are fit to data.

3. Myth: Linear measurement from ordinal test and survey data is impossible.

Fact: Ordinal data have been used as a basis for invariant linear measures for decades.

4. Myth: Scientific laws like Newton’s laws of motion cannot be successfully formulated, tested, or validated in psychology and the social sciences.

Fact: Mathematical laws of human behavior and cognition in the same form as Newton’s laws are formulated, tested, and validated in numerous Rasch model applications.

5. Myth: Experimental manipulations of psychological and social phenomena are inherently impossible or unethical.

Fact: Decades of research across multiple fields have successfully shown how theory-informed interventions on items/indicators/questions can result in predictable, consistent, and substantively meaningful quantitative changes.

6. Myth: “Real” measurement is impossible in psychology and the social sciences.

Fact: Success in predictive theory, instrument calibration, and in maintaining stable units of comparison over time are all evidence supporting the viability of meaningful uniform units of measurement in psychology and the social sciences.

7. Myth: Efficient economic markets can incorporate only manufactured and liquid capital, and property. Human, social, and natural capital, being intangible, have permanent status as market externalities as they cannot be measured well enough to enable accountability, pricing, or transferable representations (common currency instruments).

Fact: The theory and methods necessary for establishing an Intangible Assets Metric System are in hand. What’s missing is the awareness of the scientific, human, social, and economic value that would be returned from the admittedly very large investments that would be required.

References and examples are available in other posts in this blog, in my publications, or on request.

The New Information Platform No One Sees Coming

December 6, 2012

I’d like to draw your attention to a fundamentally important area of disruptive innovations no one seems to see coming. The biggest thing rising in the world of science today that does not appear to be on anyone’s radar is measurement. Transformative potential beyond that of the Internet itself is available.

Realizing that potential will require an Intangible Assets Metric System. This system will connect together all the different ways any one thing is measured, bringing common languages for representing human, social, and economic value into play everywhere. We need these metrics on the front lines of education, health care, social services, and in human, reputation, and natural resource management, as well as in the economic models and financial spreadsheets informing policy, and in the scientific research conducted in dozens of fields.

All reading ability measures, for instance, should be transparently, inexpensively, and effortlessly expressed in a universally uniform metric, in the same way that standardized measures of weight and volume inform grocery store purchasing decisions. We have made starts at such systems for reading, writing, and math ability measures, and for health status, functionality, and chronic disease management measures. There oddly seems to be, however, little awareness of the full value that stands to be gained from uniform metrics in these areas, despite the overwhelming human, economic, and scientific value derived from standardized units in the existing economy. There has accordingly been virtually no leadership or investment in this area.

Measurement practice in business is woefully out of touch with the true paradigm shift that has been underway in psychometrics for years, even though the mantra “you manage what you measure” is repeated far and wide. In a fascinating twist, practically the only ones who notice the business world’s conceptual shortfall in measurement practice are the contrarians who observe that quantification can often be more of a distraction from management than the medium of its execution—but this is true only when measures are poorly conceived, designed, and implemented.

Demand for better measurement—measurement that reduces data volume not only with no loss of information but with the addition of otherwise unavailable interstitial information; that supports mass customized comparability for informed purchasing and quality improvement decisions; and that enables common product definitions for outcomes-based budgeting—is growing hand in hand with the spread of resilient, nimble, lean, and adaptive business models, and with the ongoing geometrical growth in data volume.

An even bigger source of demand for the features of advanced measurement is the increasing dependence of the economy on intangible assets, those forms of human, social, and natural capital that comprise 90% or more of the total capital under management. We will bring these now economically dead forms of capital to life by systematically standardizing representations of their quality and quantity. The Internet is the planetary nervous system through which basic information travels, and the Intangible Assets Metric System will be the global cerebrum, where higher order thinking takes place.

It will not be possible to realize the full potential of lean thinking in the information- and service-based economy without an Intangible Assets Metric System. Given the long-proven business value of standards and the role of measurement in management, it seems self-evident that our ongoing economic difficulties stem largely from our failure to develop and deploy an Intangible Assets Metric System providing common currencies for the exchange of authentic wealth. The future of sustainable and socially responsible business practices must surely depend extensively on universal access to flexible and practical uniform metrics for intangible assets.

Of course, for global intangible assets standards to be viable, they must be adaptable to local business demands and conditions without compromising their comparability. And that is just what is most powerfully disruptive about contemporary measurement methods: they make mass customization a reality. They’ve been doing so in computerized testing since the 1970s. Isn’t it time we started putting this technology to systematic use in a wide range of applications, from human and environmental resource management to education, health care, and social services?

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 [http://www.rasch.org/rmt/rmt154j.htm].

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 [http://www.fordham.edu/economics/vinod/ehr05.htm], Pope Auditorium, Lowenstein Bldg, Fordham University.

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

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., http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2010). 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. (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. LivingCapitalMetrics.com. Retrieved 18 January 2011, from Social Science Research Network: http://ssrn.com/abstract=1739386.

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 [http://ssrn.com/abstract=2083975].

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: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

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HEY GREECE!!! One more time through the basics

May 10, 2012

As the battle between austerity and growth mindsets threatens to freeze into a brittle gridlock, it seems time once again to simplify and repeat some painfully obvious observations.

1. Human, social, and natural capital make up at least 90 percent of the capital under management in the global economy.

2. There is no system of uniform weights and measures for these forms of capital.

3. We manage what we measure; so, lacking proper measures for 90 percent of the capital in the economy, we cannot possibly manage it properly.

4. Measurement theory and practice have advanced to the point that the technical viability of a meaningful, objective, and precise system of uniform units for human, social, and natural capital is no longer an issue.

5. A metric system for intangible assets (human, social, and natural capital) is the infrastructural capacity building project capable of supporting sustainable and responsible growth we are looking for.

6. Individual citizens, philanthropists, entrepreneurs, corporations, NGOs, educators, health care advocates, innovators, researchers, and governments everywhere ought to be focusing intensely on building systems of consensus measures that take full advantage of existing technical means for instrument scaling, equating, adaptive administration, mass customization, growth modeling, data quality assessment, and diagnostic individualized reporting.

7. Uniform impact measurement will make it possible to price outcomes in ways that allow market forces to inform consumers as to where they can obtain the best cost/value relation for the money. In other words, the profit motive will be directly harnessed in growing human, social, and natural capital.

8. Happiness indexes and gross national or domestic authentic wealth products will not obtain any real practical utility until individuals, firms, NGOs, and governments can directly manage their own intangible asset bottom lines.

See other posts in this blog or the links below for more information.

William P. Fisher, Jr., Ph.D.

Research Associate
BEAR Center
Graduate School of Education
University of California, Berkeley
Principal
LivingCapitalMetrics Consulting

We are what we measure.

It’s time we measured what we want to be.

Connect with me on LinkedIn: http://www.linkedin.com/in/livingcapitalmetrics
View my research on my SSRN Author page: http://ssrn.com/author=1090685
Read my blog at https://livingcapitalmetrics.wordpress.com.
See my web site at http://www.livingcapitalmetrics.com.
http://www.rasch.org
Creative Commons License
LivingCapitalMetrics Blog by William P. Fisher, Jr., Ph.D. is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.
Based on a work at livingcapitalmetrics.wordpress.com.
Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Comments on the New ANSI Human Capital Investor Metrics Standard

April 16, 2012

The full text of the proposed standard is available here.

It’s good to see a document emerge in this area, especially one with such a broad base of support from a diverse range of stakeholders. As is stated in the standard, the metrics defined in it are a good place to start and in many instances will likely improve the quality and quantity of the information made available to investors.

There are several issues to keep in mind as the value of standards for human capital metrics becomes more widely appreciated. First, in the context of a comprehensively defined investment framework, human capital is just one of the four major forms of capital, the other three being social, natural, and manufactured (Ekins, 1992; Ekins, Dresden, and Dahlstrom, 2008). To ensure as far as possible the long term stability and sustainability of their profits, and of the economic system as a whole, investors will certainly want to expand the range of the available standards to include social and natural capital along with human capital.

Second, though we manage what we measure, investment management is seriously compromised by having high quality scientific measurement standards only for manufactured capital (length, weight, volume, temperature, energy, time, kilowatts, etc.). Over 80 years of research on ability tests, surveys, rating scales, and assessments has reached a place from which it is prepared to revolutionize the management of intangible forms of capital (Fisher, 2007, 2009a, 2009b, 2010, 2011a, 2011b; Fisher & Stenner, 2011a, 2011b; Wilson, 2011; Wright, 1999). The very large reductions in transaction costs effected by standardized metrics in the economy at large (Barzel, 1982; Benham and Benham, 2000) are likely to have a similarly profound effect on the economics of human, social, and natural capital (Fisher, 2011a, 2012a, 2012b).

The potential for dramatic change in the conceptualization of metrics is most evident in the proposed standard in the sections on leadership quality and employee engagement. For instance, in the section on leadership quality, it is stated that “Investors will be able to directly compare all organizations that are using the same vendor’s methodology.” This kind of dependency should not be allowed to stand as a significant factor in a measurement standard. Properly constructed and validated scientific measures, such as those that have been in wide use in education, psychology and health care for several decades (Andrich, 2010; Bezruzcko, 2005; Bond and Fox, 2007; Fisher and Wright, 1994; Rasch, 1960; Salzberger, 2009; Wright, 1999), are equated to a common unit. Comparability should never depend on which vendor is used. Rather, any instrument that actually measures the construct of interest (leadership quality or employee engagement) should do so in a common unit and within an acceptable range of error. “Normalizing” measures for comparability, as is suggested in the standard, means employing psychometric methods that are 50 years out of date and that are far less rigorous and practical than need be. Transparency in measurement means looking through the instrument to the thing itself. If particular instruments color or reshape what is measured, or merely change the meaning of the numbers reported, then the integrity of the standard as a standard should be re-examined.

Third, for investments in human capital to be effectively managed, each distinct aspect of it (motivations, skills and abilities, health) needs to be measured separately, just as height, weight, and temperature are. New technologies have already transformed measurement practices in ways that make the necessary processes precise and inexpensive. Of special interest are adaptively administered precalibrated instruments supporting mass customized—but globally comparable—measures (for instance, see the examples at http://blog.lexile.com/tag/oasis/ and that were presented at the recent Pearson Global Research Conference in Fremantle, Australia http://www.pearson.com.au/marketing/corporate/pearson_global/default.html; also see Wright and Bell 1984, Lunz, Bergstrom, and Gershon, 1994, Bejar, et al., 2003).

Fourth, the ownership of human capital needs clarification and legal status. If we consider each individual to own their abilities, health, and motivations, and to be solely responsible for decisions made concerning the disposition of those properties, then, in accord with their proven measured amounts of each type of human capital, everyone ought to have legal title to a specific number of shares or credits of each type. This may transform employment away from wage-based job classification compensation to an individualized investment-based continuous quality improvement platform. The same kind of legal titling system will, of course, need to be worked out for social and natural capital, as well.

Fifth, given scientific standards for each major form of capital, practical measurement technologies, and legal title to our shares of capital, we will need expanded financial accounting standards and tools for managing our individual and collective investments. Ongoing research and debates concerning these standards and tools (Siegel and Borgia, 2006; Young and Williams, 2010) have yet to connect with the larger scientific, economic, and legal issues raised here, but developments in this direction should be emerging in due course.

Sixth, a number of lingering moral, ethical and political questions are cast in a new light in this context. The significance of individual behaviors and decisions is informed and largely determined by the context of the culture and institutions in which those behaviors and decisions are executed. Many of the morally despicable but not illegal investment decisions leading to the recent economic downturn put individuals in the position of either setting themselves apart and threatening their careers or doing what was best for their portfolios within the limits of the law. Current efforts intended to devise new regulatory constraints are misguided in focusing on ever more microscopically defined particulars. What is needed is instead a system in which profits are contingent on the growth of human, social, and natural capital. In that framework, legal but ultimately unfair practices would drive down social capital stock values, counterbalancing ill-gotten gains and making them unprofitable.

Seventh, the International Vocabulary of Measurement, now in its third edition (VIM3), is a standard recognized by all eight international standards accrediting bodies (BIPM, etc.). The VIM3 (http://www.bipm.org/en/publications/guides/vim.html) and forthcoming VIM4 are intended to provide a uniform set of concepts and terms for all fields that employ measures across the natural and social sciences. A new dialogue on these issues has commenced in the context of the International Measurement Confederation (IMEKO), whose member organizations are the weights and standards measurement institutes from countries around the world (Conference note, 2011). The 2012 President of the Psychometric Society, Mark Wilson, gave an invited address at the September 2011 IMEKO meeting (Wilson, 2011), and a member of the VIM3 editorial board, Luca Mari, is invited to speak at the July, 2012 International Meeting of the Psychometric Society. I encourage all interested parties to become involved in efforts of these kinds in their own fields.

References

Andrich, D. (2010). Sufficiency and conditional estimation of person parameters in the polytomous Rasch model. Psychometrika, 75(2), 292-308.

Barzel, Y. (1982). Measurement costs and the organization of markets. Journal of Law and Economics, 25, 27-48.

Bejar, I., Lawless, R. R., Morley, M. E., Wagner, M. E., Bennett, R. E., & Revuelta, J. (2003, November). A feasibility study of on-the-fly item generation in adaptive testing. The Journal of Technology, Learning, and Assessment, 2(3), 1-29; http://ejournals.bc.edu/ojs/index.php/jtla/article/view/1663.

Benham, A., & Benham, L. (2000). Measuring the costs of exchange. In C. Ménard (Ed.), Institutions, contracts and organizations: Perspectives from new institutional economics (pp. 367-375). Cheltenham, UK: Edward Elgar.

Bezruczko, N. (Ed.). (2005). Rasch measurement in health sciences. Maple Grove, MN: JAM Press.

Bond, T., & Fox, C. (2007). Applying the Rasch model: Fundamental measurement in the human sciences, 2d edition. Mahwah, New Jersey: Lawrence Erlbaum Associates.

Conference note. (2011). IMEKO Symposium: August 31- September 2, 2011, Jena, Germany. Rasch Measurement Transactions, 25(1), 1318.

Ekins, P. (1992). A four-capital model of wealth creation. In P. Ekins & M. Max-Neef (Eds.), Real-life economics: Understanding wealth creation (pp. 147-155). London: Routledge.

Ekins, P., Dresner, S., & Dahlstrom, K. (2008). The four-capital method of sustainable development evaluation. European Environment, 18(2), 63-80.

Fisher, W. P., Jr. (2007). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

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

Fisher, W. P.. Jr. (2009b). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P.. Jr. (2010). 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. (2011a). 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. (2011b). Measurement, metrology and the coordination of sociotechnical networks. In  S. Bercea (Chair), New Education and Training Methods. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf, Jena, Germany.

Fisher, W. P., Jr. (2012a). Measure local, manage global: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (pp. in press). New York: Palgrave Macmillan.

Fisher, W. P., Jr. (2012b). What the world needs now: A bold plan for new standards. Standards Engineering, 64, in press.

Fisher, W. P., Jr., & Stenner, A. J. (2011a). Metrology for the social, behavioral, and economic sciences (Social, Behavioral, and Economic Sciences White Paper Series). Retrieved 25 October 2011, from National Science Foundation: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011b). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

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

Lunz, M. E., Bergstrom, B. A., & Gershon, R. C. (1994). Computer adaptive testing. International Journal of Educational Research, 21(6), 623-634.

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.

Salzberger, T. (2009). Measurement in marketing research: An alternative framework. Northampton, MA: Edward Elgar.

Siegel, P., & Borgia, C. (2006). The measurement and recognition of intangible assets. Journal of Business and Public Affairs, 1(1).

Wilson, M. (2011). The role of mathematical models in measurement: A perspective from psychometrics. In L. Mari (Chair), Plenary lecture. International Measurement Confederation (IMEKO), http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24178/ilm1-2011imeko-005.pdf, Jena, Germany.

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.

Wright, B. D., & Bell, S. R. (1984, Winter). Item banks: What, why, how. Journal of Educational Measurement, 21(4), 331-345 [http://www.rasch.org/memo43.htm].

Young, J. J., & Williams, P. F. (2010, August). Sorting and comparing: Standard-setting and “ethical” categories. Critical Perspectives on Accounting, 21(6), 509-521.

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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.

Knowledge and skills as the currency of 21st-century economies

March 11, 2012

In his March 11, 2012 New York Times column, Thomas Friedman quotes the OECD’s Andreas Schleicher as saying, “knowledge and skills have become the global currency of 21st-century economies, but there is no central bank that prints this currency. Everyone has to decide on their own how much they will print.” This is a very interesting thing to say, especially because it reveals some common misconceptions about currency, capital, economics, and the institutions in which they are situated.

The question raised in many of the posts in this blog concerns just what kind of bank would print this currency, and what the currency would look like. The issue is of central economic importance, as Schleicher recognizes when he says that economic stimulus certainly has a place in countering a prolonged recession, but “the only sustainable way is to grow our way out by giving more people the knowledge and skills to compete, collaborate and connect in a way that drives our countries forward.”

Following through on the currency metaphor, obvious concerns that arise from Schleicher’s comments stem from the way he conflates the idea of a currency with the value it is supposed to represent. When he says individuals have to decide how much of the currency to print, what he means is they have to decide how much education they want to accrue. This is, of course, far different from simply printing money, which, when this is done and there is no value to back it up, is a sure way to bring about rampant inflation, as Germany learned in the 1920s. Schleicher and Friedman both know this, but the capacity of the metaphor to mislead may not be readily apparent.

Another concern that comes up is why there is no central bank printing the currency for us. Of course, it might seem as though we don’t need banks to print it for us, since, if individuals can print it, then why complicate things by bringing the banks into it? But note, again, that the focus here is on the currency, and nothing is said about the unit in which it is denominated.

The unit of value is the key to the deeper root problem, which is less one of increasing people’s stocks of skills and knowledge (though that is, of course, a great thing to do) and more one of creating the institutions and systems through which we can make order-of-magnitude improvements in the way people invest in and profit from their skills and knowledge. In other words, the problem is in having as many different currencies as there are individuals.

After all, what kind of an economy would we have if the value of the US dollars I hold was different from yours, and from everyone else’s? What if we all printed our own dollars and their value changed depending on who held them (or on how many we each printed)? Everyone would pay different amounts in the grocery store. We’d all spend half our time figuring out how to convert our own currency into someone else’s.

And this is pretty much what we do when it comes to trading on the value of our investments in stocks of knowledge, skills, health, motivations, and trust, loyalty, and commitment, some of the major forms of human and social capital. When we’re able, we put a recognized name brand behind our investments by attending a prestigious university or obtaining care at a hospital known for its stellar outcomes. But proxies like these just aggregate the currencies’ values at a bit higher level of dependence on the company you keep. It doesn’t do anything to solve the problem of actually providing transferable representations you can count on to retain a predictable value in any given exchange.

The crux of the problem is that today’s institutions define the markets in which we trade human and social capital in ways that make certain assumptions, and those assumptions are counterproductive relative to other assumptions that might be made. That is, the dominant form of economic discourse takes it for granted that markets are formed by the buying and selling activities of consumers and producers, which in turn dictates the form of institutions. But this gets the process backwards (Miller and O’Leary, 2007). Markets cannot form in the absence of institutions that define the roles, rules, and relationships embodied in economic exchange, as has been pointed out by Douglass North (1981, 1990), and a very large literature on institutional economics that has emerged from the work of North and his colleagues since the late 1970s.

And so, once again, this is why I keep repeating ad nauseum the same old lines in different ways. In this case, the repetition focuses on the institutions that “print” (so to speak) the currencies in which we express and trade economic and scientific values for mass or weight (kilograms and pounds), length (meters and yards), temperature (degrees Celsius and Fahrenheit), energy (kilowatts), etc. Economic growth and growth in scientific knowledge simultaneously erupted in the 19th century after metrological systems were created to inform trade in commodities and ideas. What we need today is a new investment of resources in the creation of a new array of standardized units for human, social, and natural capital. For more information, see prior posts in this blog, and the publications listed below.

Fisher, W. P., Jr. (1997). Physical disability construct convergence across instruments: Towards a universal metric. Journal of Outcome Measurement, 1(2), 87-113.

Fisher, W. P., Jr. (1999). Foundations for health status metrology: The stability of MOS SF-36 PF-10 calibrations across samples. Journal of the Louisiana State Medical Society, 151(11), 566-578.

Fisher, W. P., Jr. (2000). Objectivity in psychosocial measurement: What, why, how. Journal of Outcome Measurement, 4(2), 527-563 [http://www.livingcapitalmetrics.com/images/WP_Fisher_Jr_2000.pdf].

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. (2003). The mathematical metaphysics of measurement and metrology: Towards meaningful quantification in the human sciences. In A. Morales (Ed.), Renascent pragmatism: Studies in law and social science (pp. 118-53). Brookfield, VT: Ashgate Publishing Co.

Fisher, W. P., Jr. (2003). Measurement and communities of inquiry. Rasch Measurement Transactions, 17(3), 936-8 [http://www.rasch.org/rmt/rmt173.pdf].

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. (2004, Wednesday, January 21). Consequences of standardized technical effects for scientific advancement. In  A. Leplège (Chair), Session 2.5A. Rasch Models: History and Philosophy. 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. (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. (2004, Friday, July 2). Relational networks and trust in the measurement of social capital. Presented at the Twelfth International Objective Measurement Workshops, Cairns, Queensland, Australia: James Cook University.

Fisher, W. P., Jr. (2005). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-179 [http://www.livingcapitalmetrics.com/images/FisherJAM05.pdf].

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 [http://www.fordham.edu/economics/vinod/ehr05.htm], Pope Auditorium, Lowenstein Bldg, Fordham University.

Fisher, W. P., Jr. (2006). Commercial measurement and academic research. Rasch Measurement Transactions, 20(2), 1058 [http://www.rasch.org/rmt/rmt202.pdf].

Fisher, W. P., Jr. (2007, Summer). Living capital metrics. Rasch Measurement Transactions, 21(1), 1092-3 [http://www.rasch.org/rmt/rmt211.pdf].

Fisher, W. P., Jr. (2007). Vanishing tricks and intellectualist condescension: Measurement, metrology, and the advancement of science. Rasch Measurement Transactions, 21(3), 1118-1121 [http://www.rasch.org/rmt/rmt213c.htm].

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 IMEKO TC1-TC7 Joint Symposium on Man, Science, and Measurement, Annecy, France: University of Savoie.

Fisher, W. P., Jr. (2009, November 19). Draft legislation on development and adoption of an intangible assets metric system. Retrieved 6 January 2011, from https://livingcapitalmetrics.wordpress.com/2009/11/19/draft-legislation/.

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. No. http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2011). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 12(1), 49-66.

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. (2011). Stochastic and historical resonances of the unit in physics and psychometrics. Measurement: Interdisciplinary Research & Perspectives, 9, 46-50.

Fisher, W. P., Jr. (2012). Measure local, manage global: Intangible assets metric standards for sustainability. In J. Marques, S. Dhiman & S. Holt (Eds.), Business administration education: Changes in management and leadership strategies (p. in press). 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, in press.

Fisher, W. P., Jr., Eubanks, R. L., & Marier, R. L. (1997, May). Health status measurement standards for electronic data sharing: Can the MOS SF36 and the LSU HSI physical functioning scales be equated?. Presented at the American Medical Informatics Association, San Jose, California.

Fisher, W. P., Jr., Harvey, R. F., & Kilgore, K. M. (1995). New developments in functional assessment: Probabilistic models for gold standards. NeuroRehabilitation, 5(1), 3-25.

Fisher, W. P., Jr., Harvey, R. F., Taylor, P., Kilgore, K. M., & Kelly, C. K. (1995, February). Rehabits: A common language of functional assessment. Archives of Physical Medicine and Rehabilitation, 76(2), 113-122.

Fisher, W. P., Jr., & Stenner, A. J. (2005, Tuesday, April 12). Creating a common market for the liberation of literacy capital. In  R. E. Schumacker (Chair), Rasch Measurement: Philosophical, Biological and Attitudinal Impacts. American Educational Research Association, Rasch Measurement SIG, Montreal, Canada.

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: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

Fisher, W. P., Jr., & Stenner, A. J. (2011, August 31 to September 2). A technology roadmap for intangible assets metrology. In Fundamentals of measurement science. International Measurement Confederation (IMEKO) TC1-TC7-TC13 Joint Symposium, http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf, Jena, Germany.

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.

North, D. C. (1981). Structure and change in economic history. New York: W. W. Norton & Co.

North, D. C. (1990). Institutions, institutional change, and economic performance. New York: Cambridge 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.
Based on a work at livingcapitalmetrics.wordpress.com.
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2011 IMEKO Conference Papers Published Online

January 13, 2012

Papers from the Joint International IMEKO TC1+ TC7+ TC13 Symposium held August 31st to September 2nd,  2011, in Jena, Germany are now available online at http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24575/IMEKO2011_TOC.pdf. The following will be of particular interest to those interested in measurement applications in the social sciences, education, health care, and psychology:

Nikolaus Bezruczko
Foundational Imperatives for Measurement with Mathematical Models
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24419/ilm1-2011imeko-030.pdf

Nikolaus Bezruczko, Shu-Pi C. Chen, Connie Hill, Joyce M. Chesniak
A Clinical Scale for Measuring Functional Caregiving of Children Assisted with Medical Technologies
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24507/ilm1-2011imeko-032.pdf

Stefan Cano, Anne F. Klassen, Andrea L. Pusic, Andrea
From Breast-Q © to Q-Score ©: Using Rasch Measurement to Better Capture Breast Surgery Outcomes
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24429/ilm1-2011imeko-039.pdf

Gordon A. Cooper, William P. Fisher, Jr.
Continuous Quantity and Unit; Their Centrality to Measurement
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24494/ilm1-2011imeko-019.pdf

William P. Fisher, Jr.
Measurement, Metrology and the Coordination of Sociotechnical Networks
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24491/ilm1-2011imeko-017.pdf

William .P Fisher, Jr., A. Jackson Stenner
A Technology Roadmap for Intangible Assets Metrology
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24493/ilm1-2011imeko-018.pdf

Carl V. Granger, Nikolaus Bezruczko
Body, Mind, and Spirit are Instrumental to Functional Health: A Case Study
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24494/ilm1-2011imeko-019.pdf

Thomas Salzberger
The Quantification of Latent Variables in the Social Sciences: Requirements for Scientific Measurement and Shortcomings of Current Procedures
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24417/ilm1-2011imeko-029.pdf

A. Jackson Stenner, Mark Stone, Donald Burdick
How to Model and Test for the Mechanisms that Make Measurement Systems Tick
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24416/ilm1-2011imeko-027.pdf

Mark Wilson
The Role of Mathematical Models in Measurement: A Perspective from Psychometrics
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24178/ilm1-2011imeko-005.pdf

Also of interest will be Karl Ruhm’s plenary lecture and papers from the Fundamentals of Measurement Science session and the Special Session on the Role of Mathematical Models in Measurement:

Karl H. Ruhm
From Verbal Models to Mathematical Models – A Didactical Concept not just in Metrology
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24167/ilm1-2011imeko-002.pdf

Alessandro Giordani, Luca Mari
Quantity and Quantity Value
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24414/ilm1-2011imeko-025.pdf

Eric Benoit
Uncertainty in Fuzzy Scales Based Measurements
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24415/ilm1-2011imeko-020.pdf

Susanne C.N. Töpfer
Application of Mathematical Models in Optical Coordinate Metrology
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24445/ilm1-2011imeko-008.pdf

Giovanni Battista Rossi
Measurement Modelling: Foundations and Probabilistic Approach
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24446/ilm1-2011imeko-009.pdf

Sanowar H. Khan, Ludwik Finkelstein
The Role of Mathematical Modelling in the Analysis and Design of Measurement Systems
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24448/ilm1-2011imeko-010.pdf

Roman Z. Morawski
Application-Oriented Approach to Mathematical Modelling of Measurement Processes
http://www.db-thueringen.de/servlets/DerivateServlet/Derivate-24449/ilm1-2011imeko-011.pdf

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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.

Open Letter on New Infrastructure as a Platform for Economic Growth and Scientific Innovation

December 21, 2011

Dear Thought Leaders Everywhere,

As you are no doubt well aware, one issue in particular is being brought to a head by the lingering economic malaise and the continuing situation in Europe: the austerity measures needed for countering debt problems are going to severely limit growth potentials, if they do not lead straight to recession or depression, unless sources of new efficiencies are found. Given the huge existing levels of debt, it is increasingly difficult to justify the capital injections the economy needs, so thinkers from Paul Krugman to Bill Clinton have proposed the possibility that some new technical infrastructure could provide a platform for new growth, much as the Internet has.

Energy might be a productive area to focus on, for instance. Others go straight to immediately available technologies, and speak of investments in existing infrastructure, such as roads and bridges. But even if a program for bringing that kind of concrete engineering up to full capacity was put in place, it would provide only a small fraction of the jobs and growth actually needed.

The basic idea is right on the mark, though no one seems to realize there are types of infrastructure beyond tangible assets like energy, or roads and bridges. Stop a second and think about it. We say we manage what we measure. Standardized weights and measures are widely recognized as an essential core feature of productivity and innovation in science, engineering, and the economy. But existing standardized metrics are exclusively focused on physics and chemistry, machines and tools, and property. And that’s the problem: manufactured capital and property make up only about 10% of all the capital under management.

What’s the other 90%? Human capital: skills, motivations, health. Social capital: trust, commitment, loyalty. Natural capital: water and air purification services, genetic variation, fisheries. Why don’t we have standardized weights and measures for managing these essential core areas of education, health care, human and natural resource management, social services, etc.? After all, if we manage what we measure, and we lack measures for the vast majority of the capital in the economy, we are probably lucky to be doing as well as we are. Our faith in efficient markets is not misplaced as much as we have not yet really made it central to the economics of every form of capital.

There are a lot of reasons why we don’t have standardized metrics for measuring individual amounts of intangible assets like human, social, and natural capital, but the supposed “subjectivity” of those forms of capital is NOT one of them. Decades of research and practice prove the viability of the technology needed for unifying the measurement of everything from literacy capital to health capital, from social capital to natural capital. What stands in our way as a society has much more to do with preconceptions and unexamined assumptions than with the supposed “soft” nature of the social sciences and psychology.

White papers published online by NIST and NSF, and a recent award-winning essay forthcoming in Standards Engineering (full references are listed below), provide rational justifications for a new research agenda focused on developing and implementing an intangible assets metric system. Such a system would enable us to act on the truth that we can accomplish far more working together cooperatively in a common framework than we can as individuals.

Better measurement is essential to better management. In the context of today’s pressing economic and social issues, new questions about the way we manage every form of resource need to be raised. You are in a position from which these questions can be effectively put forward for consideration by thought leaders across a wide array of disciplines and industries. We hope you will see fit to do so. If we can be of any further assistance, please do not hesitate to let us know. Thank you.

Sincerely,

William P. Fisher, Jr., Ph.D.

A. Jackson Stenner, Ph.D.

Fisher, W. P., Jr. (2009). NIST Critical national need idea White Paper: metrological infrastructure for human, social, and natural capital (Tech. Rep. No. http://www.nist.gov/tip/wp/pswp/upload/202_metrological_infrastructure_for_human_social_natural.pdf). Washington, DC: National Institute for Standards and Technology.

Fisher, W. P., Jr. (2012). What the world needs now: A bold plan for new standards. Standards Engineering, forthcoming. For the ANSI press release, see http://webstore.ansi.org/NewsDetail.aspx?NewsGuid=590a225c-d779-4f81-804e-4d05ef239c37.)

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: http://www.nsf.gov/sbe/sbe_2020/submission_detail.cfm?upld_id=36.

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