Archive for the ‘fabio’ Category
This semester we spent a lot of time discussing Shiao et al’s (2012) article in Sociological Theory claiming that recent genetic research provides a reason to believe that “races” exist. Now we’ll discuss the symposium that was recently published.
There are three responses by Anne Morning, Daniel Hosag, and Fujimora et al. There is a lot in there so I will focus on what I think is most important:
- Genomic analyses are contaminated by racial categories. I.e., genomic clustering results rely on social categories of race.
- Genomic analyses are inconsistent in that different algorithms producs different number of human clusters (“clinal groups”).
- Genomic analyses do not clearly map onto groups that would clearly be identitified as racial or ethnic groups.
Let me take each in turn. On a purely logical level, 1 is probably the weakest point. As I noted in my original post on Shiao et al 2012, the contamination of a scientific research program by social bias does not logically imply that the basic idea is flawed. That requires a different argument. My original example: social definitions of non-humans have plagued scientific research, but that doesn’t imply that there aren’t meaningful distinctions between fish or rocks. It only shows that a particular scientist got it wrong.
Point 2 is a much stronger point. Inconsistent results, or those that are very sensitive to initial paramters set during model estimation, should reduce our confidence. I think the respondents do a good job suggesting that genomic research does not show a clear partition of people based on genomic data.
I think Shiao (and other people on his side) have a plausible response: human populations have no clear boundaries, they intermix a bit, and we should expect fuzzy boundaries. To support this point, you would examine the distribution of the number of clusters done using different data and different methods. If we get a very “flat” posterior (i.e., any number of groups is equally possible), the critics win. If the distribution has concentrated mass and the mean is not zero, then Shiao et al wins. In other words, meta analysis is the way we settle this sort of claim. Neither side has done this analysis in the Sociological Theory exchange.
Point 3 is unpersuasive as presented. As I noted in an earlier point, it is logically possible that there is genuine clustering of people but it doesn’t match to our notions of what counts as a race. For example, maybe I am not Latino but I am Basque-Dutch-Colombian-Sub-Tico. So race exists, but not in the way we understand it. So the mismatch between genomic data and folk notions of race may be beside the point.
Shiao et al’s response hits some common points and focuses on others (e.g., their review of the genomic literature is accurate in contrast to what the critics claim). Shiao et al’s response to point 2 is a bit different in that it goes into detail about what certain algorithms accomplish.
Overall, I am struck at what was accepted by most folks. There seem to be genuine biological differences between people, behavioral genetics is not irrelevant to sociology, and there seems to be meaningful dimensions of variation among people that is tied to geography. This last point is also noted by Shiao at el. Shiao then makes a strong point – if you believe that there is genomic variation by geography, why immediately jump to the strongest constructionist argument? Doesn’t make sense.
A few months ago, I noted that I was a racial agnostic because I don’t possess the technical knowledge to judge rival claims and I don’t immediately assume the constructionist view is true. After reading this exchange, I am moving toward the view that there is indeed systematic variation in people, but “Race” might be a terribly bad way to think about it.
Question: In the movie Interstellar, what is the one thing that an advanced human race can not accomplish?
- Building a five dimensional tesseract allowing people to cross time itself.
- Making a wormhole connecting distant parts of the universe.
- Colonization and exploration of new planets.
- Letting the Black Guy live to the end of the movie.
If you said 1, 2 or 3, then you know jack about science fiction. TV Tropes has a great list: The one guy killed in The Shining is Dick Halloran; in Deep Blue Sea, Samuel Jackson is eaten by a shark; X-Men First class kills the only black character very quickly; in the Alien films, Black characters die early and fast; and so forth. Recent film isn’t much better. The last Riddick film had only 8 characters – and all 4 people of color die. At least they let Jeffrey Wright live in The Hunger Games – but only after crippling him and putting him in a wheel chair.
I had my hopes up for Interstellar. Dr. Romilly is the dude with the most brain power. You’re going to need a Ph.D. in astrophysics if the human race will be saved. So I’m like, ya, this guy will live to the end. But no!!! Blown up by Matt flippin’ Damon, fer cryin’ out loud. At least they could’ve softened the blow by tossing in Affleck.
Henry Mintzberg raises the hypothesis that business schools aren’t terribly good at training managers:
This is one question these centers of research do not study. We made an exception. A decade after its publication in 1990, I looked at a book called Inside the Harvard Business School, by David Ewing. (The first line was “The Harvard Business School is probably the most powerful private institution in the world.” Unfortunately he might have been right.) The book listed 19 Harvard alumni who “had made it to the top”—the school’s superstars as of 1990. My attention was drawn to a few people who would not have been on that list after 1990.
So Joseph Lampel and I studied the subsequent records of all 19. How did they do? In a word, badly. A majority, 10, seemed clearly to have failed, meaning that the company went bankrupt, they were forced out of the CEO chair, a major merger backfired, and so on. The performance of another 4 we found to be questionable at least. Some of these 14 CEOs built up or turned around businesses, prominently and dramatically, only to see them weaken or collapse just as dramatically.
Mintzberg also notes that few people seemed interested in his analysis. It’s like a medical school ignoring a study showing that all their graduates kills their patients.
My view on these findings is (a) I need some counter factuals – do non-MBA holders do any better? and (b) an assessment of selection effects – maybe at risk companies tend to over-recruit MBA’s in a desperate attempt to save the ship. Mintzberg is definitely onto something important. It is not entirely clear how a lot MBA training translates into making the tough decisions that CEO’s are often faced with.
Andrea Campbell has an article in Vox about the often perverse consequences of means testing in social policy. If you really need help, then means testing creates an incentive to completely spend all your assets so you can qualify. She uses the tragic case of her sister-in-law who was left paralyzed after an auto accident and now requires round the clock medical care:
Brian continued: Marcella qualified for Medi-Cal because she is disabled, but because Medi-Cal is for poor people, Dave and Marcella have to be poor to receive it-they have to “meet” the program’s “income test.” Counterintuitively, meeting the income test doesn’t mean having enough income (as in doing well on a test), but rather having low-enough income. The income test is actually an income limit.
Moreover, because Dave is employed, he and Marcella would be in a particular version of the program called “Share of Cost” Medi-Cal. It works this way: as a family of three with one disabled member, they are allowed to keep $2,100 of Dave’s $3,250 monthly earnings to live on. The rest of Dave’s earnings, $1,150, would go to Medi-Cal as the family’s share of cost. That is, any month in which Marcella incurred medical expenses, she and Dave must pay the first $1,150. To our surprise, if Dave earned more money, the extra amount would also go to Medi-Cal: the cost sharing is a 100 percent tax on Dave’s earnings. I figured out later that the $2,100 my brother and sister-in-law are to live on puts them at 133 percent of the federal poverty level for a family of three. Essentially, the way they meet the income test is for Medi-Cal to skim off Dave’s income until they are in fact poor. Brian noted that they are “lucky” that they are allowed to retain that much income; if Marcella weren’t disabled, the amount they’d be allowed to retain would be even lower than $2,100. And this is how things will be indefinitely. In order to get poor people’s health insurance, Dave and Marcella must stay poor, forever.
To make issues worse, California has an arcane system of means tested programs that make it hard to even understand what you might, or might not, be qualified for:
So much for helping my brother and sister-in-law navigate the system. Medi-Cal is a collection of more than 100 programs, each with its own income methodology and rules. A person familiar with Medi-Cal likened the program to the Winchester Mystery House, the San Jose mansion constructed continually over four decades by the odd widow of the Winchester rifle fortune: there is no master plan. “All the ‘rooms’ added on over the years makes it very difficult to see which rules apply to which groups and to follow them all the way through,” this observer told me. And even if Dave and Marcella could retain a bit more income to live on, they are still subject to the asset limit and all of Medi-Cal’s other strictures. They are still trapped in an eccentric’s mansion, where the stairways lead to ceilings and the doors open onto walls.
Campbell nails it on the head when she notes that social policy is a bizarre contraption of programs. Lesson: Make social policy simple and with wide coverage. Otherwise, don’t bother.