R1 – Response to Readings

In “Storytelling for Oppositionists and Others: a Plea for Narrative,” law professor Richard Delgado makes a wonderfully unpredictable move for an article in a law review: he gleefully spins a tale. The thrust of the article is a presentation, through a carefully wrought narrative of an event from different perspectives, of the powerfully different ways in which people and institutions may view the same sequence of events. The question at the core regards the decision of a fancy law school not to hire a black applicant for a teaching job; we see this from the school’s perspective (broadly self-acquitting and couched in terms of ultimate fairness), the applicant’s perspective (wronged, condescended to, and repeatedly disrespected), the revolutionary student’s perspective (radically angry and permanently untrusting of authority), and finally the “anonymous leafletter’s” response (a sort of balanced, careful synthesis of the best of each of the prior arguments).

Two interesting points I’d like to address about this piece: 1) The “Rashomon” version of the story (n.b. that Rashomon is in fact referenced, p. 2416 n. 24) would have us believe that the different narratives have, ultimately, some equivalent truth value. In this view, there are four different truths, all of them true in the internal honest sense of the teller of that truth—and the fact that they are mutually contradictory is just a quirk of human perception and memory. But Delgado never actually completes this stroke of the Rashomon idea: he does not grant that these truths must be permitted to coexist precariously. Rather, and never explicitly, he seems to support the notion that these different narrativizations are perhaps competing for proximity to a final truth. But the real truth, Delgado seems to support, lies somewhere at the nexus of these narrative possibilities but not equally distributed throughout them. 2) Regarding this “final truth, “ I believe there is a funny, albeit subtle, metanarrative to the story. I have no evidence other than a hunch to support this, but I believe the author was speaking to his colleagues through this article, using the voice of the “anonymous” leaflet writer as his own. Note the not-so-subtle hint dropped in the footnote of page 2431, “Like all the stories, the leaflet is purely fictional; perhaps it was born as an “internal memo,” stimulated by Al-Hammar’s speech, in the minds of many progressive listeners at the same time.” In fact this entire article may well be serving as exposition for an internal memo, published to a law review, for the benefit of the author’s colleagues.

“Micro Stories and Mega Stories” by Ramesh Jain and Malcolm Slaney serves, in my eyes, as a wonderful object lesson illustrating the failures of standard science/engineering thinking in the face of social science discussions. The piece is written syllogistically:

“In the good old days…selecting the best such events was difficult because people cannot remember many events.…Moreover, people only had a vague memory of the event experience so it was important to make those experiences as compelling as possible. Consequently, creativity or imagination is considered one of the most important factors in story creation.” (p. 88)

Where did the authors divine this ersatz insight about people’s memories and the values appreciated in storytelling in the “good old days”? It would appear out of a simple logical progression: in the authors’ narrative style, any peculiar unsupported conclusion is fine so long as it adheres to preconceived notions of story and looks good on the page. This is remarkably irresponsible!

The authors also hide behind the smoke of meaningless or unsupported generalities like “new events are happening at all levels, and these events result in new data,” and “…the difference between real and imaginary in storytelling has started to become stronger” (p. 88). Regardless, the authors do hint at an interesting idea regarding the accumulation of a great deal of “microdata” in the form of tweets, location check-ins, selfies, etc. The filtering and analysis of many microdata are then supposedly able to form “mega-stories,” which are never quite defined but seem to be things like trending search terms and estimations of crowd sentiment based on cheering sound detected. Not especially “mega,” it would seem. A further unfortunate example of mega-stories are those told by Hans Rosling…the problem with that being that Prof. Rosling’s data is not drawn from the tweets of the masses but rather the same staid organizations that have been reliably producing statistical data for years. If that’s mega-data, then it’s nothing new.