"A spectacular incident . . . had somehow eluded my attention": The Impact of Cyril Levitt and William Shaffir's book, The Riot at Christie Pits (1987)
Bibliographic record
Abstract
The year 2017 marks three decades since the 1987 publication of The Riot at Christie Pits. The book chronicles the events of August 16, 1933, when Toronto experienced one of the most violent riots in Canadian history: young Jewish men retaliated after Nazi sympathizers unfurled a swastika flag at a neighbourhood baseball game. Despite the brutality of the riot, however, it would be 54 years until scholars Cyril Levitt and William Shaffir would document the event. Why did scholars ignore it for so long? Neither Canada, Toronto, nor Jews were invested in rehashing such a dreadful incident. Since the appearance of The Riot at Christie Pits, however, attention to the riot has increased, and its legacy has been viewed in a more positive light.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.045 | 0.045 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| 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".