Review of <i>Women on the North American Plains </i> edited by Renee M. Laegreid and Sandra K. Mathews
Bibliographic record
Abstract
Despite over thirty years having elapsed since Joan Jensen and Darlis Miller, in "The Gentle Tamers Revisited," called for new approaches to western women's history, popular stereotypes of what constitutes a Great Plains woman remain deeply ingrained in the general public's imagination. Although three decades of scholarship have slowly chipped away at the typecast, until recently no one piece has consolidated the diversity of women's experiences within the Canadian and American Great Plains. We should herald, therefore, the arrival of Women on the North American Plains. This long-needed collection delivers a powerful corrective to scholarship's and popular imagery's shortcomings. The contributors recognize that there was, and is, no all-inclusive Great Plains woman. Her characteristics have always varied; she did not live in a certain time or place, have a particular religion, belong to one race or ethnicity. She was not always married, or even heterosexual. There was, and is, no one type.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".