#87: Reconciliation, Sport History, and Indigenous Peoples in Canada
Bibliographic record
Abstract
Abstract A strengths-and-hope perspective was used to explicate the process underpinning, as well as the benefits and challenges arising from the intertwining of sport history and public history in a Canadian sesquicentennial public history project. The project goal was to contribute toward the Truth and Reconciliation Final Report Call to Action #87 by ensuring that public education, in the form of Wikipedia entries on elite Indigenous athletes in Canada, would be available in an easily accessed manner and that there would be 150+ entries by the end of 2017. The pathway taken to meet that goal included a combination of personal efforts and class assignments to edit and/or create entries, along with the hosting of an editathon on elite Indigenous athletes, resulting in the 176 entries that currently exist as part of three categories: First Nations sportspeople (142 entries), Mètis sportspeople (thirty-one entries), and Canadian Inuit sportspeople (three entries).
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.027 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".