Bibliographic record
Abstract
Book reviewed in this article: EG. BAILEY, Treasons, Stratagems, and Spoils: How Leaders Make Practical Use of Beliefs and Values. HIMANI BANNERJI, SHAHRZAD MOJAB and JUDITH WHITEHEAD (eds.), Of Property and Propriety: The Role of Gender and Class in Imperialism and Nationalism. PAUL E. BRODWIN (ed.), Biotechnology and Culture: Bodies, Anxieties, Ethics. MARK BROWN and JOHN PRATT (eds.), Dangerous Offenders: Punishment and Social Order. ARDRA L. COLE and J. GARY KNOWLES (eds.), Lives in Context: The Art of Life History Research. ZILLAH EISENSTEIN, Manmade Breast Cancers. SUSAN MARTHA KAHN, Reproducing Jews: A Cultural Account of Assisted Conception in Israel. RICHARD J.F. DAY, Multiculturalism and the History of Canadian Diversity. RALPH A. LITZINGER, Other Chinas: The Yao and the Politics of National Belonging. CAROL ANN MULLER, Rituals of Fertility and the Sacrifice of Desire: Nazarite Women's Performance in South Africa. MARILYN SILVERMAN, An Irish Working Class: Explorations in Political Economy and Hegemony, 1800–1950.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.455 | 0.485 |
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".