This essay (serialized here across 24 separate posts) uses words and numbers to discuss the uses of words and numbers — particularly examining evaluations of university degrees that employ statistical data to substantiate competing claims. Statistical analyses are crudely introduced as the mode du jour of popular logic, but any ratiocinative technique could likely be inserted in this re-fillable space and applied to create and defend categories of meaning with or without quantitative support. Questions posed across the series include: Is the data informing or affirming what we believe? What are the implications of granting this approach broader authority? The author, Melanie Williams, graduated from UA in 2006, with a B.A. in Anthropology and Religious Studies.
“[I]rrational behavior in the markets may result precisely because individuals are responding rationally to their incentives.” The Signal and the Noise, p.357.
Surely the incentives for generating $tati$tical analy$e$ are the same incentives I have to keep sweeping up crayons. Molly Ball says it better:
“[P]ollsters get paid by the poll, ad makers by the ad, phone-calling firms by the call, direct-mailers by the piece. They all have an incentive to promote their services, whether or not doing so helps the campaign win—and they face few consequences if it doesn’t.”
Nate Silver’s success depends upon him nailing his forecasts. Other types of analyses may be funded whether they prove correct or no. We can assume, given the uncertainty into which these predictions are cast, they aren’t as concerned with whether or not the statistics of an unknown future will vindicate them, as they are with the more immediate demands of saying something interesting, selling more copy, meeting a deadline, responding to a critique – i.e., getting about the business of circumlocution that constitutes the ever-changing public discourse in which we participate and by so doing, authorize. I can’t debunk them – they might be right. Like Fukuyama, they’ve chosen premises that aren’t falsifiable. But as producers/consumers of this information, I think we could afford to be a bit more skeptical about the weight we give a statistical projection of a job market two, three, or five years into the future. I also just want to point out that we’re doing it – that inferences we represent as meaningful are simultaneously explanations of mathematical correlations and assertions of mathematical correlations. And if you’re like me, it’s tempting to let these assertions inform the decisions we make when we ponder the costs and benefits of choosing an educational or career path, thanks to our procrustean tendencies to apply blanket abstractions to individuals. But if I can’t assume I know anything about the creative processes of corporate CEOs based on my own stereotypes, maybe I likewise shouldn’t hold myself to projections of an unknown future based on deductions retrospectively drawn from a range of data within an arbitrary set of criteria. In the end, I am being imagined, too – just as the notion of a past is an imaginative exercise, and the assertion of a future based upon it is an extension of that conceit. These will likely always be contested, unless Fukuyama’s History plays out to its natural End – or we could say: someone else’s Beginning, Middle, or Tuesday. I’m ready to believe in the possibility of anything, now that we’ve invented Furbies. When faced with the showdown between “truth in the data” vs. “common sense,” I’ll put my money on the even chance that we’re making it up as we go along. For “what is now proved was once only imagined,” so sayeth my favorite 18th century Englishman. I’m with you, liberal arts major Newt Gingrich. Let’s colonize this moon. I bet I could get hosed there off two beers.
Part 24 coming today at noon…