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race and genomics: comments on shiao et al.

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Shiao et al in Sociological Theory, the symposioum, Scatterplot’s discussion, Andrew Perrin’s comments, last week’s discussion.

Last week, I argued that many sociologists make a strong argument. Not only are social classifications of race a convention, but there is no meaningful clustering of people that can be derived from physical or biological traits. To make this claim, I suggested that one would need to have a discussion of what meaningful traits would include, get a huge sample people, and then see if there are indeed clusters. The purpose of Shaio et al (2012) is to claim that when someone conducts such an exercise, there is some clustering.

Before I offer my own view of the evidence that Shiao et al offer, we need to set some ground rules. What are the logical possible outcomes of such an exercise?

  1. The null hypothesis: your clustering methods yield no clusters (e.g., there are no detectable sub-groups of people).
  2. The weak hypothesis: clustering algorithms yield ambiguous results. It’s like getting in regression analysis a small correlation with a p=.07. This is important because it should shift your prior moderately.
  3. The “conventional” strong hypothesis: unambiguous groups that correspond to social classifications of people. E.g., there really is a “White” group of people corresponding to people from Europe.
  4. The “unconventional” strong hypothesis: unambiguous groups that do not correspond to common social classifications of people. For example, there might be an extremely well defined group of people that combines Hawaiians and Albanians.

A few technical points, which are important. First, any such exercise will need top incorporate robustness checks because clustering methods require the use to set up initial parameters. Clustering algorithms do not tell you how many groups there are. Instead, they answer the question of how well the model fits the hypothesis that you have X groups. Second, sociologists tend to mix up these possible outcomes. They correctly point out that there is a social construction called “race” which is real in its effects and influence on people. But that doesn’t logically entail anything about the presence or absence of human populations that are differentiated due to random variation of inherent physical traits over time. Also, they fail to consider #4. Their might be actual differences, but they might not match up to our common beliefs.

So what does Shiao at al offer and where does it lie in this spectrum of possibilities? Well, the article is a not a systematic review of genomic research that searches for clusters or people. Rather, it offers a few important points drawn from anthropology and genomics. First, Shiao et al point out that there is a now undisputed (among academics) human history. Humans originated in East Africa and then spread out (“Out of Africa thesis”). Second, as people spread out, genomic variation emerges as people mate with people close by. Third, genetic drift implies that geography will predict variations in genes. As you move from X to Y, you will see measurable differences in people. Fourth, these differences are gradual in character.

Shiao then switch gears and talk about clustering of people using genomic data. They tell us that there are statistically detectable and stable group differences and that these do not rigidly determine behavior. They also cite research suggesting these statistical groups correlate with self-described racial groupings. Then, the authors discuss a “bounded” approach to social theory where biology imposes some constraints on the variation on behavior but in a non-deterministic fashion.

I’ll get to the symposium next week, but here’s my response: 1. There is a real tension. At some points, Shiao et al suggests a world of gradual variation, which suggests no distinct racial groups (outcome #1) but then there’s a big focus clusters.  2. If we do live in a world of gradual, but real, variation in human biology, then the whole clustering approach is misleading. Instead, we might live in a world that’s like a contour map. It’s all connected, there are no groups, but you see some variables increase as you move along the map. 3. If that’s true, we need an outcome #5 – “race is not real but biology is real.” 4. I definitely need more detail on the clustering methods and procedures. Some critics have pointed out that the clusters found in research are endogenously produced, which makes me suspect that the underlying science might be hovering around outcomes #1 (it all depends on the algorithm and its parameters) or #2 (there might be some clustering, but it is very poorly defined).

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Written by fabiorojas

October 20, 2014 at 12:01 am

fanfare for the common man

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From DJ M&M: “”There isn’t anything common about this–the height of prog rock IMO. Also: I like the idea of making a music video in an empty stadium during winter.” From

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Written by fabiorojas

October 19, 2014 at 12:01 am

academia against interdisciplinary work

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In response to Siri’s post about multi-disciplinary work, Peter Levin wrote the following:

For what it’s worth, working in a corporate environment, on big hairy systemic questions like, ‘How can we design an ecosystem for technologies to support precision agriculture over the next 2 decades?’ I work with a psychologist, an engineer, two anthropologists, an MBA/physicist, and a French literature PhD.

It’s a specifically-academia problem.

I agree. But I want to add a few comments. First, the evidence indicates that the problem is worse in social sciences than physical sciences. Social scientists are very territorial, as this article by Lada Adamic & co shows. Second, this system is reinforced by journal editors and tenure committees. Deans and administrators may sing the praises of interdisciplinary work, they routinely allow departments to punish faculty who don’t publish within discipline and journal editors are happy to let reviewers shoot down articles that use out of discipline ideas.

So, yes, interdisciplinary is important and needed, but until the system of rewards changes in the academy, it will remain the rhetoric of enthusiastic administrators.

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Written by fabiorojas

October 17, 2014 at 4:22 am

Posted in academia, fabio

do we need multi-disciplinary organization research? a guest post by siri ann terjesen

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Siri Ann Terjesen is an assistant professor of management and international business at Indiana University and an Associate Editor of the Academy of Management Learning & Education. She is an entrepreneurship researcher and she also does work on supply chains and related issues. This guest post addresses multidisciplinary scholarship.

I am interested in orgtheory readers’ perspectives on a critical but under-examined issue in academia, including scholarship about organizations. That is, in academia, individual scholars are incentivized to focus on a particular issue in a particular discipline and discouraged from developing deep expertise in multiple fields. For example, business scholars examine the same universe (e.g., firms, employees, etc.), albeit through different branches (disciplines such as strategy, organizational behavior, operations management, finance, accounting, ethics, law, etc.) which do not dialogue actively with one another—and there are very few academics who develop a real repertoire across multiple fields- that is, are truly multidisciplinary ‘protean’ scholars who contribute to leading journals in multiple disciplines (e.g., disciplines as distinct as ethics and operations management or accounting and organizational behavior) and have a profound influence across these distinct arenas.

This is surprising because history shows us that some of the greatest learning and paradigm shifts come from the contributions of polymaths- individuals whose expertise draws on a wide range of knowledge- from early historical examples (Francis Bacon, Erasmus, Galileo Galelei, Hildegard von Bingen, and Ben Franklin) to more recent scholars (Michael Polanyi and Linus Pauling). Researchers in the applied sciences are beginning to recognize the power of polymath, protean scholars who bring new innovations through their openness to variety and flexibility and operations across multidisciplinary spaces. There are also personal motivations- individuals who have many repertoires of knowledge may develop a broader understanding and appreciation of all human accomplishments and are personally able to enjoy the pursuit of multiple paths to excellence and to have more peak experiences across these fields. Certainly there are prevailing counterarguments concerning a Jack-of-all-Trades but master of noneand the sheer costs of operating in multiple institutions with distinct players, particularly gatekeepers. I welcome orgtheory readers’ insights and debates on this issue in any respect- theoretical perspectives, pros/cons, examples, personal experiences, etc.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power 

Written by fabiorojas

October 15, 2014 at 12:01 am

before you say race isn’t real, you need a definition of race

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This week, I’d like to focus on the sociology of race. We’ll discuss Shiao et al.’s Sociological Theory article The Genomic Challenge to the Social Construction of Race, which is the subject of a symposium. After you read the article and symposium, you might enjoy the Scatterplot discussion.

In this first post, I’d like to discuss the definitional problems associated with the concept “race.” The underlying concept is that people differ in some systematic way that goes beyond learned traits (like language). One aspect of the “person in the street” view of race is that it reflects common ancestry, which produces correlated physical and social traits. When thinking about this approach to race, most sociologists adopt the constructivist view which says that: (a) the way we group people together reflects our historical moment, not a genuine grouping of people with shared traits and  (b) the only physical differences between people are superficial.

One thing to note about the constructivist approach to race is that the first claim is very easy to defend and the other is very challenging. The classifications used by the “person on the street” are essentially fleeting social conventions. For example, Americans used the “one drop rule” to classify people, but it makes little sense because putting more weight on Black ancestors than White ancestors is arbitrary. Furthermore, ethnic classifications vary by place and even year to year. The ethnic classifications used in social practice flunk the basic tests of reliability and validity that one would want from any measurement of the social world.

The second claim is that there are no meaningful differences between people in general. This claim is much harder to make. This is not an assessment of truth of the claim, but the evidence needed to make is of a tall order. Namely, to make the strong constructivist argument, you would need (a) a definition of which traits matter, (b) a systematic measurement of those traits from a very large sample of people, (c) criteria for clustering people based on data, and (d) a clear test that all (or even most) reasonable clustering methods show a single group of people. As you can see, you need *a lot* of evidence to make that work.

That is where Shiao et al get into the game. They never dispute the first claim, but suggest that the second claim is indefensible – there is evidence of non-random clustering of people using genomic data. This is very important because it disentangles two important issues – race as social category and race as intra-group similarity. It’s like saying the Average Joe may be mistaken about air, earth, water, and fire, but real scientists can see that there are elements out there and you can do real science with them.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power 

Written by fabiorojas

October 14, 2014 at 12:04 am

funk and hirschman on derivatives

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All around super nice guys and scholars Russell Funk and Dan Hirschman have a new paper in ASQ on financial regulations. The basic idea is that new securities can slowly unravel regulatory schemes:

Regulators, much like market actors, rely on categorical distinctions. Innovations that are ambiguous to regulatory categories but not to market actors present a problem for regulators and an opportunity for innovative firms. Using a wide range of primary and secondary, qualitative and quantitative sources, we trace the history of one class of innovative financial derivatives—interest rate and foreign exchange swaps—to show how these instruments undermined the separation of commercial and investment banking established by the Glass–Steagall Act of 1933 even as overt political action failed to do so. Swaps did not fit neatly into existing product categories—futures, securities, loans—and thus evaded regulatory scrutiny for many years. The market success of swaps put commercial and investment banks into direct competition and, in so doing, undermined Glass–Steagall. Drawing on this case, we theorize that ambiguous innovations may disrupt the regulatory status quo and shift the political burden onto parties that want to maintain existing regulations. Our findings also suggest that category-spanning innovations may be more valuable to market participants if regulators find them difficult to interpret.

Read the whole paper here.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power 

Written by fabiorojas

October 13, 2014 at 4:16 am

Posted in economics, fabio, markets

the hidden gem that is NPR’s tiny desk concerts

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“… Oh, and her English cackle.” via guest DJ M&M.

50+ chapters of grad skool advice goodness: Grad Skool Rulz/From Black Power

Written by fabiorojas

October 12, 2014 at 12:14 am

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