Canada's Most Wanted: Pioneer Women on the Western Prairies*
Bibliographic record
Abstract
Cet article analyse les expériences des femmes pendant la colonisation des Prairies au Canada en mettant l'accent sur leur travail, sur leurs aptitudes et sur les capacites d'adaptation a l'environnement naturel et aux obstacles économiques auxquels ces femmes et leurs families se sont mesurés. Bien que les attitudes patriarcales domi‐nantes, la législation et les principes économiques aient quelque peu occulté les contributions des femmes, les efforts qu'elles ont déployés en Saskatchewan illustrent la «souplesse» dont ont fait preuve les fermières dans l'accomplissement de tâches productives et non productives. L'article démontre que cette souplesse a constitué un facteur déterminant de la survie des fermes familiales et, par là, du succès de l'industrie du blé. This article analyzes women's experiences during the settlement of the western prairie region of Canada. Attention is placed on their labour, skills and ability to adapt to the natural environment and the economic obstacles that they and their families encountered. While prevailing patriarchal attitudes, legislation and economic principles obscured women's contributions, the efforts of women in Saskatchewan are used to highlight the “flexibility” exhibited by farm women in performing productive and non‐productive labour. It is argued that this flexibility was critical to the survival of family farms, and thus to the success of the wheat economy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.038 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".