Archive for the ‘Internet’ Category

A Simple Example of How Better Measurement Creates New Market Efficiencies, Reduces Transaction Costs, and Enables the Pricing of Intangible Assets

March 4, 2011

One of the ironies of life is that we often overlook the obvious in favor of the obscure. And so one hears of huge resources poured into finding and capitalizing on opportunities that provide infinitesimally small returns, while other opportunities—with equally certain odds of success but far more profitable returns—are completely neglected.

The National Institute for Standards and Technology (NIST) reports returns on investment ranging from 32% to over 400% in 32 metrological improvements made in semiconductors, construction, automation, computers, materials, manufacturing, chemicals, photonics, communications and pharmaceuticals (NIST, 2009). Previous posts in this blog offer more information on the economic value of metrology. The point is that the returns obtained from improvements in the measurement of tangible assets will likely also be achieved in the measurement of intangible assets.

How? With a little bit of imagination, each stage in the development of increasingly meaningful, efficient, and useful measures described in this previous post can be seen as implying a significant return on investment. As those returns are sought, investors will coordinate and align different technologies and resources relative to a roadmap of how these stages are likely to unfold in the future, as described in this previous post. The basic concepts of how efficient and meaningful measurement reduces transaction costs and market frictions, and how it brings capital to life, are explained and documented in my publications (Fisher, 2002-2011), but what would a concrete example of the new value created look like?

The examples I have in mind hinge on the difference between counting and measuring. Counting is a natural and obvious thing to do when we need some indication of how much of something there is. But counting is not measuring (Cooper & Humphry, 2010; Wright, 1989, 1992, 1993, 1999). This is not some minor academic distinction of no practical use or consequence. It is rather the source of the vast majority of the problems we have in comparing outcome and performance measures.

Imagine how things would be if we couldn’t weigh fruit in a grocery store, and all we could do was count pieces. We can tell when eight small oranges possess less overall mass of fruit than four large ones by weighing them; the eight small oranges might weigh .75 kilograms (about 1.6 pounds) while the four large ones come in at 1.0 kilo (2.2 pounds). If oranges were sold by count instead of weight, perceptive traders would buy small oranges and make more money selling them than they could if they bought large ones.

But we can’t currently arrive so easily at the comparisons we need when we’re buying and selling intangible assets, like those produced as the outcomes of educational, health care, or other services. So I want to walk through a couple of very down-to-earth examples to bring the point home. Today we’ll focus on the simplest version of the story, and tomorrow we’ll take up a little more complicated version, dealing with the counts, percentages, and scores used in balanced scorecard and dashboard metrics of various kinds.

What if you score eight on one reading test and I score four on a different reading test? Who has more reading ability? In the same way that we might be able to tell just by looking that eight small oranges are likely to have less actual orange fruit than four big ones, we might also be able to tell just by looking that eight easy (short, common) words can likely be read correctly with less reading ability than four difficult (long, rare) words can be.

So let’s analyze the difference between buying oranges and buying reading ability. We’ll set up three scenarios for buying reading ability. In all three, we’ll imagine we’re comparing how we buy oranges with the way we would have to go about buying reading ability today if teachers were paid for the gains made on the tests they administer at the beginning and end of the school year.

In the first scenario, the teachers make up their own tests. In the second, the teachers each use a different standardized test. In the third, each teacher uses a computer program that draws questions from the same online bank of precalibrated items to construct a unique test custom tailored to each student. Reading ability scenario one is likely the most commonly found in real life. Scenario three is the rarest, but nonetheless describes a situation that has been available to millions of students in the U.S., Australia, and elsewhere for several years. Scenarios one, two and three correspond with developmental levels one, three, and five described in a previous blog entry.

Buying Oranges

When you go into one grocery store and I go into another, we don’t have any oranges with us. When we leave, I have eight and you have four. I have twice as many oranges as you, but yours weigh a kilo, about a third more than mine (.75 kilos).

When we paid for the oranges, the transaction was finished in a few seconds. Neither one of us experienced any confusion, annoyance, or inconvenience in relation to the quality of information we had on the amount of orange fruits we were buying. I did not, however, pay twice as much as you did. In fact, you paid more for yours than I did for mine, in direct proportion to the difference in the measured amounts.

No negotiations were necessary to consummate the transactions, and there was no need for special inquiries about how much orange we were buying. We knew from experience in this and other stores that the prices we paid were comparable with those offered in other times and places. Our information was cheap, as it was printed on the bag of oranges or could be read off a scale, and it was very high quality, as the measures were directly comparable with measures from any other scale in any other store. So, in buying oranges, the impact of information quality on the overall cost of the transaction was so inexpensive as to be negligible.

Buying Reading Ability (Scenario 1)

So now you and I go through third grade as eight year olds. You’re in one school and I’m in another. We have different teachers. Each teacher makes up his or her own reading tests. When we started the school year, we each took a reading test (different ones), and we took another (again, different ones) as we ended the school year.

For each test, your teacher counted up your correct answers and divided by the total number of questions; so did mine. You got 72% correct on the first one, and 94% correct on the last one. I got 83% correct on the first one, and 86% correct on the last one. Your score went up 22%, much more than the 3% mine went up. But did you learn more? It is impossible to tell. What if both of your tests were easier—not just for you or for me but for everyone—than both of mine? What if my second test was a lot harder than my first one? On the other hand, what if your tests were harder than mine? Perhaps you did even better than your scores seem to indicate.

We’ll just exclude from consideration other factors that might come to bear, such as whether your tests were significantly longer or shorter than mine, or if one of us ran out of time and did not answer a lot of questions.

If our parents had to pay the reading teacher at the end of the school year for the gains that were made, how would they tell what they were getting for their money? What if your teacher gave a hard test at the start of the year and an easy one at the end of the year so that you’d have a big gain and your parents would have to pay more? What if my teacher gave an easy test at the start of the year and a hard one at the end, so that a really high price could be put on very small gains? If our parents were to compare their experiences in buying our improved reading ability, they would have a lot of questions about how much improvement was actually obtained. They would be confused and annoyed at how inconvenient the scores are, because they are difficult, if not impossible, to compare. A lot of time and effort might be invested in examining the words and sentences in each of the four reading tests to try to determine how easy or hard they are in relation to each other. Or, more likely, everyone would throw their hands up and pay as little as they possibly can for outcomes they don’t understand.

Buying Reading Ability (Scenario 2)

In this scenario, we are third graders again, in different schools with different reading teachers. Now, instead of our teachers making up their own tests, our reading abilities are measured at the beginning and the end of the school year using two different standardized tests sold by competing testing companies. You’re in a private suburban school that’s part of an independent schools association. I’m in a public school along with dozens of others in an urban school district.

For each test, our parents received a report in the mail showing our scores. As before, we know how many questions we each answered correctly, and, unlike before, we don’t know which particular questions we got right or wrong. Finally, we don’t know how easy or hard your tests were relative to mine, but we know that the two tests you took were equated, and so were the two I took. That means your tests will show how much reading ability you gained, and so will mine.

We have one new bit of information we didn’t have before, and that’s a percentile score. Now we know that at the beginning of the year, with a percentile ranking of 72, you performed better than 72% of the other private school third graders taking this test, and at the end of the year you performed better than 76% of them. In contrast, I had percentiles of 84 and 89.

The question we have to ask now is if our parents are going to pay for the percentile gain, or for the actual gain in reading ability. You and I each learned more than our peers did on average, since our percentile scores went up, but this would not work out as a satisfactory way to pay teachers. Averages being averages, if you and I learned more and faster, someone else learned less and slower, so that, in the end, it all balances out. Are we to have teachers paying parents when their children learn less, simply redistributing money in a zero sum game?

And so, additional individualized reports are sent to our parents by the testing companies. Your tests are equated with each other, and they measure in a comparable unit that ranges from 120 to 480. You had a starting score of 235 and finished the year with a score of 420, for a gain of 185.

The tests I took are comparable and measure in the same unit, too, but not the same unit as your tests measure in. Scores on my tests range from 400 to 1200. I started the year with a score of 790, and finished at 1080, for a gain of 290.

Now the confusion in the first scenario is overcome, in part. Our parents can see that we each made real gains in reading ability. The difficulty levels of the two tests you took are the same, as are the difficulties of the two tests I took. But our parents still don’t know what to pay the teacher because they can’t tell if you or I learned more. You had lower percentiles and test scores than I did, but you are being compared with what is likely a higher scoring group of suburban and higher socioeconomic status students than the urban group of disadvantaged students I’m compared against. And your scores aren’t comparable with mine, so you might have started and finished with more reading ability than I did, or maybe I had more than you. There isn’t enough information here to tell.

So, again, the information that is provided is insufficient to the task of settling on a reasonable price for the outcomes obtained. Our parents will again be annoyed and confused by the low quality information that makes it impossible to know what to pay the teacher.

Buying Reading Ability (Scenario 3)

In the third scenario, we are still third graders in different schools with different reading teachers. This time our reading abilities are measured by tests that are completely unique. Every student has a test custom tailored to their particular ability. Unlike the tests in the first and second scenarios, however, now all of the tests have been constructed carefully on the basis of extensive data analysis and experimental tests. Different testing companies are providing the service, but they have gone to the trouble to work together to create consensus standards defining the unit of measurement for any and all reading test items.

For each test, our parents received a report in the mail showing our measures. As before, we know how many questions we each answered correctly. Now, though we don’t know which particular questions we got right or wrong, we can see typical items ordered by difficulty lined up in a way that shows us what kind of items we got wrong, and which kind we got right. And now we also know your tests were equated relative to mine, so we can compare how much reading ability you gained relative to how much I gained. Now our parents can confidently determine how much they should pay the teacher, at least in proportion to their children’s relative measures. If our measured gains are equal, the same payment can be made. If one of us obtained more value, then proportionately more should be paid.

In this third scenario, we have a situation directly analogous to buying oranges. You have a measured amount of increased reading ability that is expressed in the same unit as my gain in reading ability, just as the weights of the oranges are comparable. Further, your test items were not identical with mine, and so the difficulties of the items we took surely differed, just as the sizes of the oranges we bought did.

This third scenario could be made yet more efficient by removing the need for creating and maintaining a calibrated item bank, as described by Stenner and Stone (2003) and in the sixth developmental level in a prior blog post here. Also, additional efficiencies could be gained by unifying the interpretation of the reading ability measures, so that progress through high school can be tracked with respect to the reading demands of adult life (Williamson, 2008).

Comparison of the Purchasing Experiences

In contrast with the grocery store experience, paying for increased reading ability in the first scenario is fraught with low quality information that greatly increases the cost of the transactions. The information is of such low quality that, of course, hardly anyone bothers to go to the trouble to try to decipher it. Too much cost is associated with the effort to make it worthwhile. So, no one knows how much gain in reading ability is obtained, or what a unit gain might cost.

When a school district or educational researchers mount studies to try to find out what it costs to improve reading ability in third graders in some standardized unit, they find so much unexplained variation in the costs that they, too, raise more questions than answers.

In grocery stores and other markets, we don’t place the cost of making the value comparison on the consumer or the merchant. Instead, society as a whole picks up the cost by funding the creation and maintenance of consensus standard metrics. Until we take up the task of doing the same thing for intangible assets, we cannot expect human, social, and natural capital markets to obtain the efficiencies we take for granted in markets for tangible assets and property.

References

Cooper, G., & Humphry, S. M. (2010). The ontological distinction between units and entities. Synthese, pp. DOI 10.1007/s11229-010-9832-1.

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

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. (2005). Daredevil barnstorming to the tipping point: New aspirations for the human sciences. Journal of Applied Measurement, 6(3), 173-9 [http://www.livingcapitalmetrics.com/images/FisherJAM05.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. (2009a, November). 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 (Tech. Rep., http://www.livingcapitalmetrics.com/images/FisherNISTWhitePaper2.pdf). New Orleans: LivingCapitalMetrics.com.

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

NIST. (2009, 20 July). Outputs and outcomes of NIST laboratory research. Available: http://www.nist.gov/director/planning/studies.cfm (Accessed 1 March 2011).

Stenner, A. J., & Stone, M. (2003). Item specification vs. item banking. Rasch Measurement Transactions, 17(3), 929-30 [http://www.rasch.org/rmt/rmt173a.htm].

Williamson, G. L. (2008). A text readability continuum for postsecondary readiness. Journal of Advanced Academics, 19(4), 602-632.

Wright, B. D. (1989). Rasch model from counting right answers: Raw scores as sufficient statistics. Rasch Measurement Transactions, 3(2), 62 [http://www.rasch.org/rmt/rmt32e.htm].

Wright, B. D. (1992, Summer). Scores are not measures. Rasch Measurement Transactions, 6(1), 208 [http://www.rasch.org/rmt/rmt61n.htm].

Wright, B. D. (1993). Thinking with raw scores. Rasch Measurement Transactions, 7(2), 299-300 [http://www.rasch.org/rmt/rmt72r.htm].

Wright, B. D. (1999). Common sense for measurement. Rasch Measurement Transactions, 13(3), 704-5  [http://www.rasch.org/rmt/rmt133h.htm].

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One of the ironies of life is that we often overlook the obvious in favor of the obscure. And so one hears of huge resources poured into finding and capitalizing on opportunities that provide infinitesimally small returns, while other opportunities—with equally certain odds of success but far more profitable returns—are completely neglected.

The National Institute for Standards and Technology (NIST) reports returns on investment ranging from 32% to over 400% in 32 metrological improvements made in semiconductors, construction, automation, computers, materials, manufacturing, chemicals, photonics, communications and pharmaceuticals (NIST, 2009). Previous posts in this blog offer more information on the economic value of metrology. The point is that the returns obtained from improvements in the measurement of tangible assets will likely also be achieved in the measurement of intangible assets.

How? With a little bit of imagination, each stage in the development of increasingly meaningful, efficient, and useful measures described in this previous post can be seen as implying a significant return on investment. As those returns are sought, investors will coordinate and align different technologies and resources relative to a roadmap of how these stages are likely to unfold in the future, as described in this previous post. But what would a concrete example of the new value created look like?

The examples I have in mind hinge on the difference between counting and measuring. Counting is a natural and obvious thing to do when we need some indication of how much of something there is. But counting is not measuring (Cooper & Humphry, 2010; Wright, 1989, 1992, 1993, 1999). This is not some minor academic distinction of no practical use or consequence. It is rather the source of the vast majority of the problems we have in comparing outcome and performance measures.

Imagine how things would be if we couldn’t weigh fruit in a grocery store, and all we could do was count pieces. We can tell when eight small oranges possess less overall mass of fruit than four large ones by weighing them; the eight small oranges might weigh .75 kilograms (about 1.6 pounds) while the four large ones come in at 1.0 kilo (2.2 pounds). If oranges were sold by count instead of weight, perceptive traders would buy small oranges and make more money selling them than they could if they bought large ones.

But we can’t currently arrive so easily at the comparisons we need when we’re buying and selling intangible assets, like those produced as the outcomes of educational, health care, or other services. So I want to walk through a couple of very down-to-earth examples to bring the point home. Today we’ll focus on the simplest version of the story, and tomorrow we’ll take up a little more complicated version, dealing with the counts, percentages, and scores used in balanced scorecard and dashboard metrics of various kinds.

What if you score eight on one reading test and I score four on a different reading test? Who has more reading ability? In the same way that we might be able to tell just by looking that eight small oranges are likely to have less actual orange fruit than four big ones, we might also be able to tell just by looking that eight easy (short, common) words can likely be read correctly with less reading ability than four difficult (long, rare) words can be.

So let’s analyze the difference between buying oranges and buying reading ability. We’ll set up three scenarios for buying reading ability. In all three, we’ll imagine we’re comparing how we buy oranges with the way we would have to go about buying reading ability today if teachers were paid for the gains made on the tests they administer at the beginning and end of the school year.

In the first scenario, the teachers make up their own tests. In the second, the teachers each use a different standardized test. In the third, each teacher uses a computer program that draws questions from the same online bank of precalibrated items to construct a unique test custom tailored to each student. Reading ability scenario one is likely the most commonly found in real life. Scenario three is the rarest, but nonetheless describes a situation that has been available to millions of students in the U.S., Australia, and elsewhere for several years. Scenarios one, two and three correspond with developmental levels one, three, and five described in a previous blog entry.

Buying Oranges

When you go into one grocery store and I go into another, we don’t have any oranges with us. When we leave, I have eight and you have four. I have twice as many oranges as you, but yours weigh a kilo, about a third more than mine (.75 kilos).

When we paid for the oranges, the transaction was finished in a few seconds. Neither one of us experienced any confusion, annoyance, or inconvenience in relation to the quality of information we had on the amount of orange fruits we were buying. I did not, however, pay twice as much as you did. In fact, you paid more for yours than I did for mine, in direct proportion to the difference in the measured amounts.

No negotiations were necessary to consummate the transactions, and there was no need for special inquiries about how much orange we were buying. We knew from experience in this and other stores that the prices we paid were comparable with those offered in other times and places. Our information was cheap, as it was printed on the bag of oranges or could be read off a scale, and it was very high quality, as the measures were directly comparable with measures from any other scale in any other store. So, in buying oranges, the impact of information quality on the overall cost of the transaction was so inexpensive as to be negligible.

Buying Reading Ability (Scenario 1)

So now you and I go through third grade as eight year olds. You’re in one school and I’m in another. We have different teachers. Each teacher makes up his or her own reading tests. When we started the school year, we each took a reading test (different ones), and we took another (again, different ones) as we ended the school year.

For each test, your teacher counted up your correct answers and divided by the total number of questions; so did mine. You got 72% correct on the first one, and 94% correct on the last one. I got 83% correct on the first one, and 86% correct on the last one. Your score went up 22%, much more than the 3% mine went up. But did you learn more? It is impossible to tell. What if both of your tests were easier—not just for you or for me but for everyone—than both of mine? What if my second test was a lot harder than my first one? On the other hand, what if your tests were harder than mine? Perhaps you did even better than your scores seem to indicate.

We’ll just exclude from consideration other factors that might come to bear, such as whether your tests were significantly longer or shorter than mine, or if one of us ran out of time and did not answer a lot of questions.

If our parents had to pay the reading teacher at the end of the school year for the gains that were made, how would they tell what they were getting for their money? What if your teacher gave a hard test at the start of the year and an easy one at the end of the year so that you’d have a big gain and your parents would have to pay more? What if my teacher gave an easy test at the start of the year and a hard one at the end, so that a really high price could be put on very small gains? If our parents were to compare their experiences in buying our improved reading ability, they would have a lot of questions about how much improvement was actually obtained. They would be confused and annoyed at how inconvenient the scores are, because they are difficult, if not impossible, to compare. A lot of time and effort might be invested in examining the words and sentences in each of the four reading tests to try to determine how easy or hard they are in relation to each other. Or, more likely, everyone would throw their hands up and pay as little as they possibly can for outcomes they don’t understand.

Buying Reading Ability (Scenario 2)

In this scenario, we are third graders again, in different schools with different reading teachers. Now, instead of our teachers making up their own tests, our reading abilities are measured at the beginning and the end of the school year using two different standardized tests sold by competing testing companies. You’re in a private suburban school that’s part of an independent schools association. I’m in a public school along with dozens of others in an urban school district.

For each test, our parents received a report in the mail showing our scores. As before, we know how many questions we each answered correctly, and, as before, we don’t know which particular questions we got right or wrong. Finally, we don’t know how easy or hard your tests were relative to mine, but we know that the two tests you took were equated, and so were the two I took. That means your tests will show how much reading ability you gained, and so will mine.

But we have one new bit of information we didn’t have before, and that’s a percentile score. Now we know that at the beginning of the year, with a percentile ranking of 72, you performed better than 72% of the other private school third graders taking this test, and at the end of the year you performed better than 76% of them. In contrast, I had percentiles of 84 and 89.

The question we have to ask now is if our parents are going to pay for the percentile gain, or for the actual gain in reading ability. You and I each learned more than our peers did on average, since our percentile scores went up, but this would not work out as a satisfactory way to pay teachers. Averages being averages, if you and I learned more and faster, someone else learned less and slower, so that, in the end, it all balances out. Are we to have teachers paying parents when their children learn less, simply redistributing money in a zero sum game?

And so, additional individualized reports are sent to our parents by the testing companies. Your tests are equated with each other, so they measure in a comparable unit that ranges from 120 to 480. You had a starting score of 235 and finished the year with a score of 420, for a gain of 185.

The tests I took are comparable and measure in the same unit, too, but not the same unit as your tests measure in. Scores on my tests range from 400 to 1200. I started the year with a score of 790, and finished at 1080, for a gain of 290.

Now the confusion in the first scenario is overcome, in part. Our parents can see that we each made real gains in reading ability. The difficulty levels of the two tests you took are the same, as are the difficulties of the two tests I took. But our parents still don’t know what to pay the teacher because they can’t tell if you or I learned more. You had lower percentiles and test scores than I did, but you are being compared with what is likely a higher scoring group of suburban and higher socioeconomic status students than the urban group of disadvantaged students I’m compared against. And your scores aren’t comparable with mine, so you might have started and finished with more reading ability than I did, or maybe I had more than you. There isn’t enough information here to tell.

So, again, the information that is provided is insufficient to the task of settling on a reasonable price for the outcomes obtained. Our parents will again be annoyed and confused by the low quality information that makes it impossible to know what to pay the teacher.

Buying Reading Ability (Scenario 3)

In the third scenario, we are still third graders in different schools with different reading teachers. This time our reading abilities are measured by tests that are completely unique. Every student has a test custom tailored to their particular ability. Unlike the tests in the first and second scenarios, however, now all of the tests have been constructed carefully on the basis of extensive data analysis and experimental tests. Different testing companies are providing the service, but they have gone to the trouble to work together to create consensus standards defining the unit of measurement for any and all reading test items.

For each test, our parents received a report in the mail showing our measures. As before, we know how many questions we each answered correctly. Now, though we don’t know which particular questions we got right or wrong, we can see typical items ordered by difficulty lined up in a way that shows us what kind of items we got wrong, and which kind we got right. And now we also know your tests were equated relative to mine, so we can compare how much reading ability you gained relative to how much I gained. Now our parents can confidently determine how much they should pay the teacher, at least in proportion to their children’s relative measures. If our measured gains are equal, the same payment can be made. If one of us obtained more value, then proportionately more should be paid.

In this third scenario, we have a situation directly analogous to buying oranges. You have a measured amount of increased reading ability that is expressed in the same unit as my gain in reading ability, just as the weights of the oranges are comparable. Further, your test items were not identical with mine, and so the difficulties of the items we took surely differed, just as the sizes of the oranges we bought did.

This third scenario could be made yet more efficient by removing the need for creating and maintaining a calibrated item bank, as described by Stenner and Stone (2003) and in the sixth developmental level in a prior blog post here. Also, additional efficiencies could be gained by unifying the interpretation of the reading ability measures, so that progress through high school can be tracked with respect to the reading demands of adult life (Williamson, 2008).

Comparison of the Purchasing Experiences

In contrast with the grocery store experience, paying for increased reading ability in the first scenario is fraught with low quality information that greatly increases the cost of the transactions. The information is of such low quality that, of course, hardly anyone bothers to go to the trouble to try to decipher it. Too much cost is associated with the effort to make it worthwhile. So, no one knows how much gain in reading ability is obtained, or what a unit gain might cost.

When a school district or educational researchers mount studies to try to find out what it costs to improve reading ability in third graders in some standardized unit, they find so much unexplained variation in the costs that they, too, raise more questions than answers.

But we don’t place the cost of making the value comparison on the consumer or the merchant in the grocery store. Instead, society as a whole picks up the cost by funding the creation and maintenance of consensus standard metrics. Until we take up the task of doing the same thing for intangible assets, we cannot expect human, social, and natural capital markets to obtain the efficiencies we take for granted in markets for tangible assets and property.

References

Cooper, G., & Humphry, S. M. (2010). The ontological distinction between units and entities. Synthese, pp. DOI 10.1007/s11229-010-9832-1.

NIST. (2009, 20 July). Outputs and outcomes of NIST laboratory research. Available: http://www.nist.gov/director/planning/studies.cfm (Accessed 1 March 2011).

Stenner, A. J., & Stone, M. (2003). Item specification vs. item banking. Rasch Measurement Transactions, 17(3), 929-30 [http://www.rasch.org/rmt/rmt173a.htm].

Williamson, G. L. (2008). A text readability continuum for postsecondary readiness. Journal of Advanced Academics, 19(4), 602-632.

Wright, B. D. (1989). Rasch model from counting right answers: Raw scores as sufficient statistics. Rasch Measurement Transactions, 3(2), 62 [http://www.rasch.org/rmt/rmt32e.htm].

Wright, B. D. (1992, Summer). Scores are not measures. Rasch Measurement Transactions, 6(1), 208 [http://www.rasch.org/rmt/rmt61n.htm].

Wright, B. D. (1993). Thinking with raw scores. Rasch Measurement Transactions, 7(2), 299-300 [http://www.rasch.org/rmt/rmt72r.htm].

Wright, B. D. (1999). Common sense for measurement. Rasch Measurement Transactions, 13(3), 704-5  [http://www.rasch.org/rmt/rmt133h.htm].

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How to Trade “Global Mush” for Beauty, Meaning, and Value: Reflections on Lanier’s New Book

January 15, 2010

Implicit in many of my recent posts here is the idea that we must learn how to follow through on the appropriation of meaning to proper ownership of the properties characteristic of our own proprietary capital resources: the creativities, abilities, skills, talents, health, motivations, trust, etc.  that make us each reliable citizens and neighbors, and economically viable in being hireable, promotable, productive, and retainable. Individual control of investment in, income from, and returns on our own shares of human, social, and natural capital ought to be a fundamental constitutional human right.

But, just as property rights are constitutionally guaranteed by nations around the world that don’t take the trouble to enforce them or even to provide their necessary infrastructural capacities, so, too, are human rights to equal opportunities widely guaranteed without being properly provided for or enforced. And now in the Internet age, we have succeeded in innovating ever more fluid media for the expression of our individual capacities for making original cultural, technical, and human contributions, but we have yet to figure out how to exert effective control over the returns and income generated by these contributions.

Jaron Lanier’s new book, “You Are Not a Gadget,” is taking up this theme in interesting ways. In his recent Wall Street Journal article, Lanier says:

“There’s a dominant dogma in the online culture of the moment that collectives make the best stuff, but it hasn’t proven to be true. The most sophisticated, influential and lucrative examples of computer code—like the page-rank algorithms in the top search engines or Adobe’s Flash— always turn out to be the results of proprietary development. Indeed, the adored iPhone came out of what many regard as the most closed, tyrannically managed software-development shop on Earth.

Actually, Silicon Valley is remarkably good at not making collectivization mistakes when our own fortunes are at stake. On the one hand we want to avoid physical work and instead benefit from intellectual property. On the other hand, we’re undermining intellectual property so that information can roam around for nothing, or more precisely as bait for advertisements. That’s a formula that leaves no way for our nation to earn a living in the long term.
The “open” paradigm rests on the assumption that the way to get ahead is to give away your brain’s work—your music, writing, computer code and so on—and earn kudos instead of money. You are then supposedly compensated because your occasional dollop of online recognition will help you get some kind of less cerebral work that can earn money. For instance, maybe you can sell custom branded T-shirts.
We’re well over a decade into this utopia of demonetized sharing and almost everyone who does the kind of work that has been collectivized online is getting poorer. There are only a tiny handful of writers or musicians who actually make a living in the new utopia, for instance. Almost everyone else is becoming more like a peasant every day.”
Lanier’s suggestions of revised software structures and micropayment systems in an extension of intellectual property rights correctly recognizes the scope of the challenges we face. He also describes the motivations driving the ongoing collectivization process, saying that “youthful fascination with collectivism is in part simply a way to address perceived ‘unfairness’.” This radical way of enforcing a very low lowest common denominator points straight at the essential problem, and that problem is apparent in the repeated use of the key word, collective.

It was not so long ago that it was impossible to use that word without immediately evoking images of Soviet central planning and committees. The “global mush” of mediocrity Lanier complains about as a direct result of collective thinking is a very good way of describing the failures of socialism that brought down the Soviet Union by undercutting its economic viability. Lanier speaks of growing up and enthusiastically participating various forms of collective life, like food co-ops and shared housing. I, too, have shared those experiences. I saw, as Lanier sees and as the members of communes in the U.S. during the 1960s saw, that nothing gets done when no one owns the process and stands to reap the rewards: when housekeeping is everyone’s responsibility, no one does it.

Further and more to the point, nothing goes right when supply and demand are dictated by a central committee driven by ideological assumptions concerning exactly what does and does not constitute the greater good.  On the contrary, innovation is stifled, inefficiencies are rampant, and no one takes the initiative to do better because there are no incentives for doing so. Though considerable pain is experienced in allowing the invisible hand to coordinate the flux and flows of markets, no better path to prosperity has yet been found. The current struggle is less one of figuring out how to do without markets than it is one of figuring out how to organize them for greater long term stability. As previous posts in this blog endeavor to show, we ought to be looking more toward bringing all forms of capital into the market instead of toward regulating some to death while others ravage the economy, scot-free.

Friedrich von Hayek (1988, 1994) is an economist and philosopher often noted for his on-target evaluations of the errors of socialism. He tellingly focused on the difference between the laborious micromanagement of socialism’s thought police and the wealth-creating liberation of capital’s capacity for self-organization. It is interesting that Lanier describes the effects of demonetized online sharing as driving most of us toward peasant status, as Hayek (1994) describes socialism as a “road to serfdom.” Of course, capitalism itself is far from perfect, since private property, and manufactured and liquid capital, have enjoyed a freedom of movement that too often recklessly tramples human rights, community life, and the natural environment. But as is described in a previous blog I posted on re-inventing capitalism, we can go a long way toward rectifying the errors of capitalism by setting up the rules of law that will lubricate and improve the efficiency of human, social, and natural capital markets.

Now, I’ve always been fascinated with the Latin root shared in words like property, propriety, proprietary, appropriation, proper, and the French propre (which means both clean and one’s own, or belonging to oneself, depending on whether it comes before or after the noun; une maison propre = a clean house and sa propre maison = his/her own house). I was then happy to encounter in graduate school Ricoeur’s (1981) theory of text interpretation, which focuses on the way we create meaning by appropriating it. Real understanding requires that we must make a text our own if we are to be able to give proper evidence of understanding it by restating or summarizing it in our own words.

Such restating is, of course, also the criterion for demonstrating that a scientific theory of the properties of a phenomenon is adequate to the task of reproducing its effects on demand. As Ricoeur (1981, p. 210) says, situating science in a sphere of signs puts the human and natural sciences together on the same footing in the context of linguistically-mediated social relations. This unification of the sciences has profound consequences, not just for philosophy, the social sciences, or economics, but for the practical task of transforming the current “global mush” into a beautiful, meaningful, and effective living creativity system. So, there is real practical significance in realizing what appropriation is and how its processes feed into our conceptualizations of property, propriety, and ownership.

When we can devise a new instrument or measuring method that gives the same results as an existing instrument or method, we have demonstrated theoretical control over the properties of the phenomenon (Heelan, 1983, 2001; Ihde, 1991; Ihde & Selinger, 2003; Fisher, 2004, 2006, 2010b). The more precisely the effects are reproduced, the purer they become, the clearer their representation, and the greater their independence from the local contingencies of sample, instrument, observer, method, etc. When we can package a technique for reproducing the desired effects (radio or tv broadcast/reception, vibrating toothbrushes, or what have you), we can export the phenomenon from the laboratory via networks of distribution, supply, sales, marketing, manufacture, repair, etc. (Latour, 1987). Proprietary methods, instruments, and effects can then be patented and ownership secured.

What we have in the current “global mush” of collective aggregations are nothing at all of this kind. There are specific criteria for information quality and network configuration (Akkerman, et al., 2007; Latour, 1987, pp. 247-257; Latour, 1995; Magnus, 2007; Mandel, 1978; Wise, 1995) that have to be met for collective cognition to realize its potential in the manner described by Surowiecki (2004) or Brafman and Beckstrom (2006), for instance.  The difference is the difference between living and dead capital, between capitalism and socialism, and between scientific measurement and funny numbers that don’t stand for the repetitive additivity of a constant unit (Fisher, 2002, 2009, 2010a). As Lanier notes, Silicon Valley understands very well the nature of this difference, and protects its own interests by vigilantly ensuring that its collective cognitions are based in properly constructed information and networks.

And here we find the crux of the lesson to be learned. We need to focus very carefully on the details of how we create meaningful relationships, of how things come into words, of how instruments are calibrated and linked together in shared systems of signification, and of how economies thrive on the productive efficiencies of well-lubricated markets. Everything we need to turn things around is available, though seeing things for what they are is one of the most daunting and difficult tasks we can undertake.

The postmodern implications of the way appropriation is more a letting-go than a possessing (Ricoeur, 1981, p. 191) will be taken up another time, in the context of the playful flow of signification we are always already caught up within. For now, it is enough to point the way toward the issues raised and examined in other posts in this blog as to how capital is brought to life. We are well on the way toward a convergence of efforts that may well result in exactly the kind of fierce individuals and competing teams able to reap their just due, as Lanier envisions.

References

Akkerman, S., Van den Bossche, P., Admiraal, W., Gijselaers, W., Segers, M., Simons, R.-J., Kirschnerd, P. (2007, February). Reconsidering group cognition: From conceptual confusion to a boundary area between cognitive and socio-cultural perspectives? Educational Research Review, 2, 39-63.
Brafman, O., & Beckstrom, R. A. (2006). The starfish and the spider: The unstoppable power of leaderless organizations. New York: Portfolio (Penguin Group).

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, 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. (2006). Meaningfulness, sufficiency, invariance, and conjoint additivity. Rasch Measurement Transactions, 20(1), 1053 [http://www.rasch.org/rmt/rmt201.htm].

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

Fisher, W. P., Jr. (2010a). Bringing human, social, and natural capital to life: Practical consequences and opportunities. Journal of Applied Measurement, 11, in press [http://www.livingcapitalmetrics.com/images/BringingHSN_FisherARMII.pdf].

Fisher, W. P., Jr. (2010)b. Reducible or irreducible? Mathematical reasoning and the ontological method. Journal of Applied Measurement, 11, in press.

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

von Hayek, F. A. (1994/1944). The road to serfdom (Fiftieth Anniversary Edition; Introduction by Milton Friedman). Chicago: University of Chicago Press.

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

Heelan, P. A. (2001). The lifeworld and scientific interpretation. In S. K. Toombs (Ed.), Handbook of phenomenology and medicine (pp. 47-66). Chicago: University of Chicago Press.

Ihde, D., & Selinger, E. (Eds.). (2003). Chasing technoscience: Matrix for materiality. (Indiana Series in Philosophy of Technology). Bloomington, Indiana: Indiana University Press.
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. New York: Cambridge University Press.

Latour, B. (1995). Cogito ergo sumus! Or psychology swept inside out by the fresh air of the upper deck: Review of Hutchins’ Cognition in the Wild, MIT Press, 1995. Mind, Culture, and Activity: An International Journal, 3(192), 54-63.

Magnus, P. D. (2007). Distributed cognition and the task of science. Social Studies of Science, 37(2), 297-310.

Mandel, J. (1978, December). Interlaboratory testing. ASTM Standardization News, 6, 11-12.

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

Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations. New York: Doubleday.
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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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Permissions beyond the scope of this license may be available at http://www.livingcapitalmetrics.com.

Contrasting Network Communities: Transparent, Efficient, and Invested vs Not

November 30, 2009

Different networks and different communities have different amounts of social capital going for them. As was originally described by Putnam (1993), some networks are organized hierarchically in a command-and-control structure. The top layers here are the autocrats, nobility, or bosses who run the show. Rigid conformity is the name of the game to get by. Those in power can make or break anyone. Market transactions in this context are characterized by the thumb on the scale, the bribe, and the kickback. Everyone is watching out for themselves.

At the opposite extreme are horizontal networks characterized by altruism and a sense that doing what’s good for everyone will eventually come back around to be good for me. The ideal here is a republic in which the law rules and everyone has the same price of entry into the market.

What I’d like to focus on is what’s going on in these horizontal networks. What makes one a more tightly-knit community than another? The closeness people feel should not be oppressive or claustrophic or smothering. I’m thinking of community relations in which people feel safe, not just personally but creatively. How and when are diversity, dissent and innovation not just tolerated but celebrated? What makes it possible for a market in new ideas and new ways of doing things to take off?

And how does a community like this differ from another one that is just as horizontally structured but that does not give rise to anything at all creative?

The answers to all of these questions seem to me to hinge on the transparency, efficiency, and volume of investments in the relationships making up the networks. What kinds of investments? All kinds: emotional, social, intellectual, financial, spiritual, etc. Less transparent, inefficient, and low volume investments don’t have the thickness or complexity of the relationships that we can see through, that are well lubricated, and that are reinforced with frequent visits.

Putnam (1993, p. 183) has a very illuminating way of putting this: “The harmonies of a choral society illustrate how voluntary collaboration can create value that no individual, no matter how wealthy, no matter how wily, could produce alone.” Social capital is the coordination of thought and behavior that embodies trust, good will, and loyalty. Social capital is at play when an individual can rely on a thickly elaborated network of largely unknown others who provide clean water, nutritious food, effective public health practices (sanitation, restaurant inspections, and sewers), fire and police protection, a fair and just judiciary, electrical and information technology, affordably priced consumer goods, medical care, and who ensure the future by educating the next generation.

Life would be incredibly difficult if we could not trust others to obey traffic laws, or to do their jobs without taking unfair advantage of access to special knowledge (credit card numbers, cash, inside information), etc. But beyond that, we gain huge efficiencies in our lives because of the way our thoughts and behaviors are harmonized and coordinated on mass scales. We just simply do not have to worry about millions of things that are being taken care of, things that would completely freeze us in our tracks if they weren’t being done.

Thus, later on the same page, Putnam also observes that, “For political stability, for government effectiveness, and even for economic progress social capital may be even more important than physical or human capital.” And so, he says, “Where norms and networks of civic engagement are lacking, the outlook for collective action appears bleak.”

But what if two communities have identical norms and networks, but they differ in one crucial way: one relies on everyday language, used in conversations and written messages, to get things done, and the other has a new language, one with a heightened capacity for transparent meaningfulness and precision efficiency? Which one is likely to be more creative and innovative?

The question can be re-expressed in terms of Gladwell’s (2000) sense of the factors contributing to reaching a tipping point: the mavens, connectors, salespeople, and the stickiness of the messages. What if the mavens in two communities are equally knowledgeable, the connectors just as interconnected, and the salespeople just as persuasive, but messages are dramatically less sticky in one community than the other? In one network of networks, saying things once gets the right response 99% of the time, but in the other things have to be repeated seven times before the right response comes back even 50% of the time, and hardly anyone makes the effort to repeat things that many times. Guess which community will be safer, more creative, and thriving?

All of this, of course, is just another way to bring out the importance of improved measurement for improving network quality and community life. As Surowiecki put it in The Wisdom of Crowds, the SARS virus was sequenced in a matter of weeks by a network of labs sharing common technical standards; without those standards, it would have taken any one of them weeks to do the same job alone. The messages these labs sent back and forth had an elevated stickiness index because they were more transparently and efficiently codified than messages were back in the days before the technical standards were created.

So the question emerges, given the means to create common languages with enhanced stickiness properties, such as we have in advanced measurement models, what kinds of creativity and innovation can we expect when these languages are introduced in the domains of human, social, and natural capital markets? That is the question of the age, it seems to me…

Gladwell, M. (2000). The tipping point: How little things can make a big difference. Boston: Little, Brown, and Company.

Putnam, R. D. (1993). Making democracy work: Civic traditions in modern Italy. Princeton, New Jersey: Princeton University Press.

Surowiecki, J. (2004). The wisdom of crowds: Why the many are smarter than the few and how collective wisdom shapes business, economies, societies and nations. New York: Doubleday.

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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.