On Beginnings: Part 24

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’m not yet convinced that outcomes outside of a closed system are knowable in advance.  If they were, Olestra would have been marketed as a purgative, Ford Motor Company would have redesigned the Pinto, and I never would’ve sat through a vivid description of The Human Centipede.  It isn’t possible to say definitively whether any course you pursue – college or otherwise – will be fruitful.  Today, you might tell the pollster it has not been “worth it.”  Tomorrow, it might seem like everything in your life was leading to this moment.  Then again, maybe I’m wrong, and there is some positivistic truth we can attain and harness to build that better future, if we can only gather enough evidence.  I wonder whose truth, and whose future, it will be?

Maybe the problem with history is precisely that we try to “learn” from it – to extrapolate futures or justify assertions based on past events – to construct “meaning” from happenstance, which we then term “progress.”  This is partly how we come to define ourselves, in the characters, ideas, and values we either venerate or view with a *mote* of superiority.  Likewise, attempts to imagine the future may be meaningful, not in some vague, power-of-becoming sense, but in what they reveal about our own subjective presuppositions, which necessarily determine the ways in which we collect, organize, and analyze data, and hash out what, after all, constitutes data in the first place.  Perhaps this is why methodology is important – an aspect of data-gathering I never considered before getting my statistically worthless B.A.  To the extent that statistical analyses may be employed to either create or diminish uncertainty, depending on the context and goals of the user, it may be more useful to think of them as yet another strategy for authorizing a certain paradigm, rather than an algorithmic gyre toward a fated singularity.  We are the noisemakers, after all, and the modulators.  We might draw own measures from the gutter to the stars, or leap into the abyss but find, as another great philosopher said, “it only goes up to your knees.” Maybe we need this king-of-the-mountain battle over “truths” to continually re-present our own idiosyncratic cosmographies – a perpetual audit of what we think we can control and what we know damn well we can’t control:  enough “reality” to reassure us that we will make it through the day, and enough “uncertainty” to cling to the sometimes smug, sometimes despondent knowledge that we are not at the mercy of statistics, whatever we may choose.  Or as liberal arts major Stephen Sondheim melodiously put it:

“Who knows what may
be lurking on the journey?
Into the woods
To get the thing
That makes it worth
the journeying.”

On Beginnings: Part 23

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 futureI 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…

On Beginnings: Part 22

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.

 

In a side-effect sense, I can offer one abiding perquisite of a liberal arts degree:  the flexibility it gives you to respond to the unfair inquiry, “So what are you going to do with a degree in _______?”  Devise any occupation you please – I plan to: “pursue a Ph.D. in topology with a special focus on knot theory,” “write choose-your-own-adventure intergalactic erotica – I’ll post a link to my blog on your wall,” “become the CEO of Goldman Sachs then coast into the office of U.S. Treasury Secretary,” “invest in a crystal ball and tell my own future for $5 a reading.  You owe me $5.”  The nebulous aegis of the College of Arts and Sciences virtually guarantees that nothing will breach the bulwarks of tenability.  Like a brisk volley by liberal arts dropout Billie Jean King, your newly forged critical thinking skills and subtle finesse of plausible diversions will deliver an ersatz sense of authority that makes your “chosen” field seem respectable while marginalizing you just enough to abate any further lines of invasive questioning.  This will buy you some time while you wait to hear back about that incredible unpaid internship opportunity!

Game, set, match.

Godspeed, Civil Engineers.  I don’t know how to help you.

If my resumé is categorically non-traditional, I am curious to know from which “traditional career pathways” current struggling college majors are deviating.  What outcomes of “success” or “failure” are we assuming, and according to whom?  What is the unspoken destiny college grads are failing to fulfill when we don’t secure “jobs in our chosen fields?”  Or to frame the question differently, what not-so-subtle classism is implied by the expectation that college graduates won’t be carpenters, or plumbers, or welders, or the inventors of meat tea?  Who says the post-bacc lifestyle is the only variety worth aspiring to, making the choice before us merely college or not-college – disregarding all the rich and interesting things people do when they walk, apparently naked and unformed as a forgotten Hugga Bunch into the wild, wonderful, cruel void?  I would wager it’s as easy to predict the future value of a college degree in a changing economy as it is to predict the day-to-day performance of the stock market – not unpredictable exactly, but as far as I know, to the degree it may be deterministic, we do not flatter ourselves that we grasp its tangled workings.  At least, liberal arts major Robert Shiller and clarinetist Alan Greenspan seem to agree on this point.   So why spin these studies, and engage in a tautological, courtroom-like contest of spectacle?

Part 23 coming tomorrow morning…

On Beginnings: Part 21

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 don’t know how to calculate the abstract value of degrees I don’t have, so I’ll talk about a few things I think I know, and wish I had known sooner rather than later.  I didn’t progress through college based on anything like cognitive ability, creative skills, or academic merit.  I got into and through college because I had parents who signed a promissory note to put me there.  If college is the filtering process that is portrayed in these many articles, it is not the “realization” of latent academic “potential.”  It is merely the line between those who can afford to pay and those who cannot afford to pay.  I graduated from UA’s College of Arts and Sciences with two of the bleakest majors these articles have rated, though I think their combined score vaults me into the range of, maybe, the college of Social Work.  I have used any means at my disposal to land all of the low-paying jobs I have had since graduation, to wit:  apply, persist, cajole, or (only twice so far!) lie.  Most of the time, if I discuss it at all, I tell people I earned a B.A. in the same blasé tone of voice I would use to tell them I once had a benign tumor, and I receive the same heartfelt tones of sympathy.  If you put stock in such things, you could easily put me into the category of the 25th percentile for whom college was not a good investment.  This has nothing to do with the “absolute” economic or social value of obtaining a degree; it’s a consequence of the decisions I have made along the way as I stumbled through my wayward life.   A more graceful, clever person, with or without a degree, may have maneuvered more successfully, however that may be defined.  Perhaps it’s the opportunity itself that’s priceless, and you can either make use of it or squander it.  But on any given day – clipboard in hand – how will you know the difference?  Continue reading

On Beginnings: Part 20

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.

 

All I set out to examine is the highly connected, highly contingent, and insular type of dialogue that informs conventional knowledge – whether it’s science, pop culture, or technological trend – whose re-presentation as “truth” is doing some behind-the-curtain work. And to ask, then, if we should be mindful of the questions we pose, of the methods we use to frame the data we select, and the ends toward which we strive in analyzing that data?  In the case of these many articles and studies rating the worth of university education vis-à-vis any other course of life, is the question really fair?  Should we expect any choice we make to have some degree of intrinsic, immutable value?  Maybe “facts” have a more precarious existence than we like to believe, since they require continued corroboration to retain their reverent status as “fact,” and since countless bits of information so categorized we later brusquely tossed under the bus. The models we use to view certain issues in certain ways aren’t really stable – they’re formed and re-formed in the arenas of their respective discursive participants. Methodologies change constantly in light of new circumstances and cross-examinations. This may have been Baseball-Bill James’s point:  We assemble meaningful collections of data to respond to a question, which in turn will likely generate another question. This is the basic form of the peer-review process academics and researchers use to exchange the ideas that occupy them and affect the rest of us, if at all, with an aura of natural progression. But peer-review-style dialogue doesn’t reduce all submissions down to the “truth;” it’s just a mechanisms of conservation – an organized way to sustain the debates over the meanings of signs within shared paradigms.  My diversion into the issues I take with the Big Data trend stems from these distinctions, since large aggregates of data seem to be used to authorize certain assertions that – due to the fact that math is even employed – lends a degree of inscrutability that keeps people from challenging the associated narratives.  And why shouldn’t we challenge them?  In this regard, I love statistical analyses, not because they provide definitive or non-definitive answers, but because they often raise questions about answers we thought we had in the bag.  To return to the popular discourse on the real, imagined, spiritual or economic merits of a college education:  there likely is no inherent value to a degree whose usefulness you will not be able to predict. There is no correct path to a career you probably won’t plan.  It may not be helpful to assume people will have any definitive opinion of the usefulness of their degree – or any type of training, for that matter.  Many of us pursue whatever will occupy us for the moment, but we may very well change our minds in 6 months, 2 years, or, if you’re like me, I can’t remember what we were talking about.

Part 21 coming tomorrow morning…

On Beginnings: Part 19

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.

 

We probably debate the touchstones of “a quality education” because we really don’t know what they are – we trust various institutions to provide the service they describe and in which they claim expertise.  If there were strict standards of pedagogy in post-secondary education aside from the bloodless quotas of financial viability and publication rates, they would likely be just as problematic as attempting to determine the “value” of the degrees peddled therein.  So who is drawing the lines of academic rites within which we are expected to operate?  And what if we are drawing them ourselves?  I would place the various articles I’ve read, along with every variety of poll, into the same category of untraceable authority claims in Baudrillard’s circulation of power, in that the “authorities” are the very consumers of the authorizing media that distribute the study.  The evidence implies the hypothesis that predicts the evidence, in a “gigantic circumvolution.”

“Thus all the messages in the media function in a similar fashion: neither information nor communication, but referendum, perpetual test, circular response, verification of the code.” Continue reading

On Beginnings: Part 18

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.

 

“The signal is the truth. The noise is what distracts us from the truth.”  The Signal and the Noise, p.17.

I wonder how the truth would appear when we found it, and who would validate it once and for all?  Should we assume collections of data “contain” essential “truths” about our own behavior that we can use to reliably predict our future choices?  Or do such statistical and probabilistic applications just plow little furrows where we nurture some irreproachable Mr. Potato Head of signification, permitting us to place and re-place any provisional features?  If so, it might benefit us to be mindful of the selections we make when, for instance, we cite probabilities to plug the gap between indecision and action.  If we place too much trust in what we perceive to be the predictive power of statistical inferences, we may be nonplussed when they inevitably fail to provide exactly the information we think we need.  Then again, there are plenty of times when we conveniently ignore information, statistical or otherwise, when it is at cross purposes to our agenda.  We may allow statistical inference to drive our behavior in ways not otherwise rational; or poo-poo marginal conclusions based on statistical surveys that turned out to have some merit, after all.

Data analyses may also lead us to make inferences not substantiated by the numbers, as in this little gem, describing another PayScale study:

“All these caveats are true. But overall, the PayScale study surely overstates the financial value of a college education. It does not compare graduates’ earnings to what they would have earned, had they skipped college. (That number is unknowable.) It compares their earnings to those of people who did not go to college—many of whom did not go because they were not clever enough to get in. Thus, some of the premium that graduates earn simply reflects the fact that they are, on average, more intelligent than non-graduates.”

I would be interested to see the data that rendered concrete notions of what constitutes intelligence, who has it, who doesn’t, what varieties they possess, and in what measure.  I suspect we can’t easily determine such things.  Or rather, we all can, and freely do.

Part 19 coming tomorrow morning…

On Beginnings: Part 17

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.

 

“We can perhaps never know the truth with 100% certainty, but making correct predictions is the way to tell if we’re getting closer.”  The Signal and the Noise, p. 255.

You can probably guess what I’m going to ask next:  What is randomness?  Is it the quirky and irreducible unpredictability of nature, at the level of the smallest particle?  Or is randomness a temporary inconvenience, an illusion of uncertainty that is really just a lamentable lack of data?  It may seem like a tedious argument, or a matter of semantics, or completely irrelevant to the topic at hand – but our reception of statistical data has a lot to do with how we define and describe randomness, and how much agency we give it in our wider senses of the universe.  If you believe in a deterministic connect-the-dot universe, what seems like chance is rather an unfortunate consequence of the dots we don’t yet see, but can build a better means of detecting.  If you believe in stochastic processes as a fundamental concept of natural phenomena, we can’t say for sure what the hell the dots are doing, or if they can be said to “be” there at all. Continue reading

On Beginnings: Part 16

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.

 

In 1814 the mathematician and astronomer Pierre-Simon Laplace published a now-famed postulate:

“”We may regard the present state of the universe as the effect of its past and the cause of its future. An intellect which at any given moment knew all of the forces that animate nature and the mutual positions of the beings that compose it, if this intellect were vast enough to submit the data to analysis, could condense into a single formula the movement of the greatest bodies of the universe and that of the lightest atom; for such an intellect nothing could be uncertain and the future just like the past would be present before its eyes.”

Complex systems have historically defied attempts at deterministic approaches, not least because the feedback concept of a dynamic system introduces chance, even in an environment in which other variables may be controlled.  “Laplace’s demon,” then, is considered an outmoded approach to physics, but the philosophy of determinism can still be seen in the data-gathering approach of the Digital Age.  The goal needn’t be a harmonious unified theory.  It is enough to take the idea of a lossless network of causation to move along to the next question, heuristically, Bayesian-like, keeping what works and discarding what doesn’t.  Continue reading

On Beginnings: Part 15

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.

 

Maybe another Bill James can offer a non-definitive answer, allowing us to move on to the next question:

“When one views the world with no definite theological bias one way or the other, one sees that order and disorder, as we now recognize them, are purely human inventions.  We are interested in certain types of arrangement, useful, aesthetic, or moral, – so interested that whenever we find them realized, the fact emphatically rivets our attention.  The result is that we work over the contents of the world selectively.  It is overflowing with disorderly arrangements from our point of view, but order is the only thing we care for and look at, and by choosing, one can always find some sort of orderly arrangement in the midst of any chaos…Our dealings with Nature are just like this.  She is a vast plenum in which our attention draws capricious lines in innumerable directions.  We count and name whatever lies upon the special lines we trace, whilst the other things and the untraced lines are neither named nor counted.”  Continue reading