Janice Forsyth, Reclaiming Tom Long Boat: Indigenous Self-Determination in Canadian Sport. With a Foreword by Willie Littlechild.
Bibliographic record
Abstract
Established in 1951, the Tom Longboat Awards seek to “recognize Aboriginal athletes for their outstanding contributions to sport in Canada.” In her meticulous work of cultural history, the Cree kinesiologist Janice Forsyth places this official discourse in settler-colonial context. “The history of sport and physical activity in Canada,” she clarifies for sports scholars and administrators, “is not a history of empowerment or inclusion, or even of opportunity, accommodation, or amalgamation. Rather, it is a history of containment, control, and elimination.” Forsyth’s incisive analysis consequently goes well beyond the fields of sociology and sport history. On my reading, her work makes major contributions to the respective fields of oblivion studies and Indigenous law.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".