Stephen Heathorn, <b><i>For Home, Country, and Race: Constructing Gender, Class, and Englishness in the Elementary School, 1880–1914.</i></b> Toronto: University of Toronto Press, 2000. 288 pp. $50.00 cloth
Bibliographic record
Abstract
In For Home, Country, and Race, Stephen Heathorn sets out to explain the “how” of English nationalism at the turn of the twentieth century. Rejecting the imperial propagandist theme, Heathorn argues that nationalist agendas in English schools were the product of educators. Accordingly, Heathorn's research focuses on the classroom as the site of nationalist education. Heathorn argues that through educational activities, especially school readers, middle-class educators brought the English working class into their nationalist hegemony. As the book's title suggests, this hegemonic view also promoted class and gender subordination. As Heathorn concludes, the proof of the working class's acceptance of this nationalist hegemony is found in their willingness “to sacrifice their lives and loved ones” in the “cataclysmic clash of rival nationalisms that erupted in 1914” (218).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".