Bibliographic record
Abstract
Scholarly depictions of the history of Aboriginal people in Canada have changed dramatically since the 1970s when Arthur J. (“Skip”) Ray entered the field. New Histories for Old examines this transformation while extending the scholarship on Canada’s Aboriginal history in new directions. The collection combines essays by prominent senior historians, geographers, and anthropologists with contributions by new voices in these fields. The chapters reflect the core themes studied by Ray himself, including Native struggles for land and resources under colonialism, the fur trade, “Indian” policy and treaties, mobility and migration, disease and well-being, and Native-newcomer relations. This book sheds new light on the history of scholarship on Canada’s Aboriginal past and the leading role played by one of Canada’s foremost historians. It also provides a fascinating snapshot of the lines of inquiry pursued by emerging scholars in the field. New Histories for Old is a major contribution to understanding Native-newcomerrelations, Native struggles for land and resources under colonialism, “Indian” policy and treaties, mobility and migration, disease and well-being, and questions about “doing” Native history. It will appeal to scholars and students in history, Native studies, geography, anthropology, and related fields.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".