Bibliographic record
Abstract
Honouring anthropologist Richard J. Preston and his outstanding career with the Crees in northern Quebec, Together We Survive presents new research by Preston's colleagues, former students, and family members who - like him - have established long-term, respectful research partnerships and friendships with Aboriginal communities. Demonstrating the influential nature of Preston's collaborative approach on anthropologists in Canada and beyond, the essays in Together We Survive explore development and urbanization, material culture, and conflict. Scholars who conducted research in the 1960s with Crees farther to the south broaden the scope of Preston's Cree Narrative (2002). A Cree colleague and friend expands on his study of traditional Cree songs. Other essays widen the geographical, historical, and cultural foci of the book beyond the Quebec Crees, examining the significance of a beaded hood at Red River in 1844, scrutinizing symbols of Anishinaabe identity, and describing the struggle for indigenous human rights at the United Nations. Building on Preston's pioneering work in cultural anthropology, Together We Survive recounts the ways in which the eastern James Bay Cree and other aboriginal peoples, faced with massive incursions on their lands and lives, have collaborated and formed respectful partnerships as they seek to survive and thrive in peace. Contributors include Regna Darnell (Western), Harvey A. Feit (McMaster), John S. Long (Nipissing), Stan L. Louttit, Richard T. McCutcheon (Algoma), the late Cath Oberholtzer (Trent), Laura Peers (Oxford), Jennifer Preston, Susan Preston, Adrian Tanner (Memorial) and Cory Willmott (Southern Illinois).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.005 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.292 | 0.134 |
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".