The Overuse of Data

Data is all around us.  Baseball teams use batting averages and on-base percentages to determine the value of their players (my New York Mets seem to fall short in this department).  Scientists test medications and compile lab results to determine the effectiveness and safety of said medications.  Such data is important to essential things like how an organization operates and whether lives are saved.

However, there are times when data can’t fully measure the human experience.  My university (along with most other universities) is constantly collecting data to measure student satisfaction.  These are done through surveys, with questions like “The instructor was typically punctual in meeting this course.”  And the usual numerical response.  5: Strongly agree. 4: Agree.  1: Strongly disagree.  And there’s a blank text box in which students can give information not typically answered in the questions.  In my experience, most students don’t fill this information out, which is why give them my own survey with open-ended questions like, “What do you like about this course?” and “What could be improved about the course?”

Numbers can’t always capture the full experience, which is why I’m often skeptical of empirical studies.  Surveys can’t capture whether one of my students couldn’t complete an assignment because they were up all night caring for a sick mother or baby.  Questionnaires don’t reveal that a player may be slumping because they’re going through a nasty divorce.  And, to be fair, sports fans don’t care about the latter.  They just want their players to perform and their teams to win.

As a Singles Studies scholar/activist, I sometimes cite data.  My favorite piece is those studies that show that single women are happier than married women, while the opposite applies to men.  This was once cited by a scholar named Paul Dolan in his 2019 book, Happy Ever After.  It’s been referred to by those of us in the singlehood community.  I’m not trained in data collection and analysis, so I tend to take the experts’ word.  I did this in the piece I recently published in Ms. Magazine.

I posted this to the Singlehood Studies listserv.  Exactly thirty-five minutes after I posted, a colleague emailed with a congratulations and just to point out that the Dolan study had been debunked.  They were even kind enough to include a link to the Reddit page.

So here’s my issue.  It’s not that this person pointed out the debunking, even though that’s not totally correct. Another colleague informed me that it was just the saying that women indicated they were happier when their spouse wasn’t in the room, which I thought was more of a cheeky remark from Dolan rather than a finding.  And to me, it sounded more like poor word choice than inaccurate data representation.  And it doesn’t negate the finding.

The issue is: was this celebration really the correct space to point out a tiny inaccuracy in data?  As academics, we have a tendency to prize knowledge above all else.  And if you’re a scientist, that knowledge had better be data-driven.  But there are times when this type of analysis isn’t called for.  I’m not a data scientist, but even I know that one can cherry pick data to unconsciously (or, sadly, consciously) confirm their biases.  This last sentence was paraphrased straight from a friend of mine who works with data.  A similar study, cited in a 1991 book called Backlash: The Undeclared War Against American Women, found that sixty percent of women surveyed indicated they were happier than their married friends.  That year again, 1991.

I don’t know if that data is accurate.  I wasn’t there when the researchers collected their data or analyzed it, and I’m not fluent in those numerical modes of expression.  In fact, when I teach my second-year writing students to read those academic articles, I tell them to skip those methodology sections and go straight to the Discussion and Conclusion sections.  This is common advice among composition pedagogues.  But I digress.

Numerical data doesn’t always capture the full experience.  And even if Dolan’s finding was inaccurate, pieces like mine help give singles a voice.  They encourage us singletons to advocate for ourselves and others.  In the five days since this piece was published, I’ve been thanked by quite a few people for it.  A notable exception:

From Mconservative Mayer, a self-proclaimed anti-feminist on Facebook: Perhaps Craig Wynne should read "Men and Marriage" by George Gilder. It's about just what the title suggests - "men and marriage" - and what happens to men AND to society, when they don't.
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Yeah.  A far-right source from 1986.  Really on the money there.  I’ll continue to use the data in a way that serves the public, not the ego of someone who misread a social cue just to pontificate a data point, and certainly not some ghost from the last time my Mets won the World Series.