The Victoria Schuck Award: A Sonata for Gender Politics Scholarship
Bibliographic record
Abstract
Even as this issue of Politics & Gender appears in print, a committee of scholars (Kimberly Morgan, Vanita Seth, and Wendy Gunther-Canada in 2011) is serving the discipline by undertaking the fascinating and painful task of choosing a book (or books) upon which to bestow the American Political Science Association's Victoria Schuck Award for Best Book on Gender Politics. Twenty three committees have given the award to 32 books since the first awards were made in 1988. The Schuck Award is one of only four association-wide book awards (the others, of course, are the Ralph Bunche Award for ethnic and cultural pluralism; the Gladys Kammerer Award for best book in U.S. national policy; and the Woodrow Wilson Award for Best Book as chosen by the Woodrow Wilson Foundation on government, politics, or international relations). How did the young field of gender politics reach such heights of scholarly recognition so soon?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.067 | 0.023 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".