The Politics of a Good Picture: Race, Class, and Form in Jeff Wall's<i>Mimic</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mimic (1982) is an early and much discussed picture by the Canadian photographer Jeff Wall, with the discussion centering largely on two topics: its subject matter and its setting (fig. 1). The subject is racism, and in this regard Mimic is “characteristic,” as Wall's best critic, Michael Fried, has observed, “of Wall's engagement in his art of the 1980s with social issues” (Why 235). Subsequently, as Fried also notes, “Wall has tended to distance himself from the overtly political concerns that are front and center in works like Mimic” (64). Indeed, in recent interviews Wall has insisted on this distance, remarking, for example, that “[t]wenty-five years ago I thought subject matter had some significance in itself” and going on to say that “Mimic was about racism in some way, about hostile gestures between races, but I'm glad the picture itself is good and it doesn't need that to be successful. Now I try to eliminate any additional subject matter—those things are for other people, they're not my problem” (Denes). His point here is not exactly that Mimic isn't antiracist—actually, its antiracism is so obvious and uncontroversial that a recent critic, Régis Michel, has complained that it “verges on political correctness” (63). The idea is rather that the success of the picture—the fact that it's a “good” picture—has nothing to do with those politics. Which leaves open the question of whether the picture's success has nothing to do with any politics or nothing to do with the particular politics of antiracism. In other words, is the picture's success independent of politics as such? Or is there a politics of the good picture?
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it