The Difficulties of Combating Inequality in Time
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
Scholars have argued that disadvantaged groups face an impossible choice in their efforts to win policies capable of diminishing inequality: whether to emphasize their sameness to or difference from the advantaged group. We analyze three cases from the 1980s and 1990s in which reformers sought to avoid that dilemma and assert groups’ sameness and difference in novel ways: in U.S. policy on biomedical research, in the European Union's initiatives on gender equality, and in Canadian law on Indigenous rights. In each case, however, the reforms adopted ultimately reproduced the sameness/difference dilemma rather than transcended it. To explain why, we show how profound disagreements about both the histories of the groups included in the policy and the place of the policy in a longer historical trajectory of reform either went unrecognized or were actively obscured. Targeted groups came to be attributed a biological or timeless essence, not because this was inevitable, we argue, but because of these failures to historicize inequality.
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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