The Edmonton and District Stragglers: gendered strategies of treaty and scrip, 1876-1886
Bibliographic record
Abstract
Metis women listed as Edmonton and District Stragglers made strategic familial and economic decisions during the treaty and scrip period of the nineteenth century. In so doing, they influenced the development and administration of the Canadian government's treaty and scrip policies. Department of Indian Affairs Inspector Thomas Wadsworth created the straggler classification as an expedient solution to a bureaucratic problem -a way to pay people who, by not belonging to an Indian band, were behaving in a way policy makers had not anticipated. The deconstruction of ethnic and band categories reveals that aboriginal women used administrative categories, including 'straggler,' 'Indian,' and 'halfbreed,' in ways unexpected by government authorities. The ways women used these categories of rule had long-term implications. Their decisions influenced their descendants' ethnic identities. Furthermore, official policy was far different from practice. When individuals responded differently than expected, new administrative categories and policies were created to accommodate for the discrepancies between expected and actual responses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.012 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".