What is Rigor?

Two years ago, my department created a new two-course, doctoral-level sequence primarily aimed at our quantitative methods students. This sequence, aside from our students, also attracts students from other departments (primarily in the social sciences) that plan to pursue more advanced methodological coursework (e.g., Hierarchical Linear Modeling).

One of the primary characteristics that differentiates this new sequence of courses from the other doctoral sequence of methodology courses that we teach is that it is “more rigorous”. This adjective, rigorous, bothers me. It bothers me because I don’t know what it means.

How do I know if a class is rigorous? When I ask my colleagues, the response is more often than not akin to Supreme Court Justice Potter Stewart’s “definition” of pornography (see Jacobellis v. Ohio)…I may not be able to define what a ‘rigorous course’ is, but you’ll know it when you take one.

It seems that students, in my experience, associate rigor with the amount (and maybe complexity) of mathematics that appear in the course. Rigor also seems to be directly associated with the amount of homework and difficulty-level of the assessments.

I think that I relate rigor to the degree to which a student is pushed intellectually. Because of this, I have a hard time associating rigor with a particular course. In my mind, rigorousness is an interaction between the content, the assessment and the student. The exact same course taught in different semesters (or different sections within a semester) has, in my mind, had differing levels of rigor, not because the content (nor assessment) has changed, but because the student make-up has been different.

The experience in the classroom, as much as we try to standardize it in the curriculum, is very different from one class to the next. A single question or curiosity might change the tenor of a class (to the good or the bad). And, try as I might to recreate the thoughtful questions or digressions of learning in future iterations of the course, the academic result often never matches that of the original.

So maybe having students that are all interested in statistics in a single course lead to a more nuanced curiosity and thereby rigor. But, on the other hand, there is much to be said about courses in which there are students with a variety of backgrounds and academic interests. I think rigor can exist in both types of courses. Or, maybe I am completely wrong and rigor is something more tangible. Is there such a thing as a rigorous course?

Here’s Looking At You!

What do we fear more?  Losing data privacy to our government, or to corporate entities?  On the one hand, we (still) have oversight over our government.  On the other hand, the government is (still) more powerful than most corporate entities, and so perhaps better situated to frighten.

In these times of Snowden and the NSA, the L.A. Times ran an interesting story about just what tracking various internet companies perform.  And it’s alarming. (“They’re watching your every move.”, July 10, 2013). Interestingly, the story does not seem to appear on their website as of this posting.)  Like the government, most of these companies claim that (a) their ‘snooping’ is algorithmic; no human sees the data and (b) their data are anonymized.  And yet…

To my knowledge, businesses aren’t required to adhere to, or even acknowledge, any standards or practices for dealing with private data.  Thus, a human could snoop on particular data.  We are left to ponder what that human will do with the information.  In the best case scenario, the human would be fired, as, according to the L.A. Times, Google did when it fired an engineer for snooping on emails of some teenage girls.

But the data are anonymous, you say?  Well, there’s anonymous and then there’s anonymous.  As LaTanya Sweeney taught us in the 90’s, knowing a person’s zipcode, gender, and date of birth is sufficient to uniquely identify 85% of Americans.  And the L.A. Times reports a similar study where just four hours of anonymized tracking data was sufficient to identify 95% of all individuals examined.  So while your name might not be recorded, by merging enough data files, they will know it is you.

This article fits in really nicely with a fascinating, revelatory book I’m currently midway through:  Jaron Lanier‘s Who Owns The Future? A basic theme of this book is that internet technology devalues products and goods (files) and values  services (software).  One process through which this happens is that we humans accept the marvelous free stuff that the internet provides (free google searches, free amazon shipping, easily pirated music files) in exchange for allowing companies to snoop. The companies turn our aggregated data into dollars by selling to advertisers.

A side affect of this, Lanier explains, is that there is a loss of social freedom.  At some point, a service such as Facebook gets to be so large that failing to join means that you are losing out on possibly rich social interactions.  (Yes, I know there are those who walk among us who refuse to join Facebook.  But these people are probably not reading this blog, particularly since our tracking ‘bots tell us that most of our readers come from Facebook referrals.  Oops.  Was I allowed to reveal that?)  So perhaps you shouldn’t complain about being snooped on since you signed away your privacy rights. (You did read the entire user agreement, right?  Raise your hand if you did.  Thought so.)  On the other hand, if you don’t sign, you become a social pariah.  (Well, an exaggeration.  For now.)

Recently, I installed Ghostery, which tracks the automated snoopers that follow me during my browsing.  Not only “tracks”, but also blocks.  Go ahead and try it.  It’s surprising how many different sources are following your every on-line move.

I have mixed feelings about blocking this data flow. The data-snooping industry is big business, and is responsible, in part, for the boom of stats majors and, more importantly, the boom in stats employment.  And so indirectly, data-snooping is paying for my income.  Lanier has an interesting solution:  individuals should be paid for their data, particular when it leads to value.  This means the era of ‘free’ is over–we might end up paying for searches and for reading wikipedia.  But he makes a persuasive case that the benefits exceed the costs.  (Well, I’m only half-way through the book.  But so far, the case is persuasive.)