Spreadsheet Politics

So a week ago I posted this page, which includes a spreadsheet of all the books I’ve ever read, and a bunch of information about them. That page gives a bit of information about why I’ve done what I’ve done. But I think it’s also important to say a couple of things about the politics of the spreadsheet (so I won’t talk about the content here, because I hope to cover that elsewhere).

Firstly, the spreadsheet, as an object, is very interested in issues of race and gender; it came about as a way of measuring (and hopefully correcting) the disproportionate weight I gave to white people and to men in my reading. But, of course, any analysis hastily and amateurishly put together is going to be an extremely blunt tool to think about such important, huge, delicate issues; when it was just for me, it didn’t necessarily matter. Now I’m at least putatively sharing it, I feel like those things are more important.

Having a category called ‘Race’, for example, which divides people neatly into ‘People of Colour’ and ‘White’ is all kinds of problematic (would ‘ethnicity’ be better? Is ‘race’ essentially a myth? Glad to take advice on this if anyone has it). Likewise, allowing only ‘Male’ and ‘Female’ for Gender is fucked up, and doesn’t come close to representing either what I feel about the complexities of that system of categorisation, or how I think we should approach questions of demographic categorisation at all. Any defence of myself would come from the fact that what I originally wanted to know was how violently skewed my reading was towards books by white people, by men, and by white men. This kind of graph wouldn’t be possible without this kind of crushing, erasing, flattening effect – I think it’s one of the problems with any quantifying project like this: it erases or elides huge swathes of human experience. For that I’m sorry.

Similarly, the ‘Nationality’ column is deeply problematic. That is, my fairly rudimentary spreadsheeting knowledge hasn’t really allowed me to acknowledge mixed or otherwise complex nationalities. Very very often I’ve been forced to simplify, divide or straight-up mistake people’s nationalities (Wikipedia is about the deepest research tool I have time to use, here). I know this is unsatisfactory; it might be actually actively offensive. And yet I want to be able to record, broadly, where the people whose books I was reading came from. Mostly I’ve gone for the nationality mentioned first on the author’s Wikipedia page (so Chinese-American writers get listed as ‘Chinese’, for example). From there, the ‘Majority/Minority World’ column takes the data from the author’s nationality, and assigns them a ‘Majority’ tag unless they’re from one of the countries included in this list of developed countries. Once again, reductive and stupid: yes. But I’d like to claim that I’m forced into this position by a combination of my own ignorance and my lack of time. As always, solutions gratefully received.

Another problem, of course, is the implication this spreadsheet seems to make that somebody’s race and gender are somehow the most important aspects of their identity. There’s no column to acknowledge disability, class, sexuality, trans- or cis-gender, choice of personal pronouns, and so on. The reason I don’t mention these things is that they’re generally much harder to ascertain from a brief skim of a Wikipedia page. Again, time- and data-restraints force me into a politically dissatisfying position.

I’m sure there are other problems that haven’t even occured to me, not to mention probably-rampant inaccuracies. Comments and thoughts (particularly but not exclusively from people who aren’t cis-het white men) are welcomed.


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