Bibliographic record
Abstract
Abstract Overexposed famous histories of Black people in the West often lead to mainstream oversimplification, relegate racial tensions to the past or elsewhere, and label them a closed chapter. These histories produce curated, uncontextualized grand narratives. The Canadian sport context is particularly fertile ground to explore the silencing of Blackness in national public histories. For instance, Jackie Robinson's 1946 debut with the Montreal Royals was more than the sanitized Canada-the-good moment reflected in Heritage Minutes. While shortened histories can be useful portals into complex sociohistorical narratives for the public, left to themselves, they deny complexity, often for political purposes. I argue that history of sport scholars need to be deliberate in publicly underscoring the “seriousness” of sport, not by themselves, but as a collective. This means more involvement in public sport history to provide an often-missing critical perspective. There are a variety of methods at historians’ disposal to begin working in tandem with each other and with other nonacademic stakeholders invested in public sport history. Using a Black Canadian lens, this essay adds a currently absent perspective to the discussion of the state of public sport history to illustrate directions for an enhanced presence of the work of historians of sport outside academia. I discuss best practices using examples of some historians’ efforts to provide critical, intersectional, and visible counternarratives alongside various other sport stakeholders, from journalists to halls of fame, and through multiple formats.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.013 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.047 | 0.015 |
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".