Bibliographic record
Abstract
n i t y c h a n g e d r a d i c a l ly between 1905 and 1945 and forever altered the face of the city.A visitor to Canada's largest metropolis at the beginning of the twentieth century would have encountered a society sharply divided according to religious and linguistic lines based on the country's two charter groups: an economically and politically dominant English-speaking Protestant community and the urban elite of Quebec's mainly rural French-Catholic majority.Sandwiched between them was a tiny Jewish population of largely anglicized Jews that included a small but growing minority of Yiddish-speaking recent Jewish immigrants from Eastern Europe.In the next decades, spurred by the mass exodus of Jews from Eastern Europe, Yiddish would put down roots as a Jewish lingua franca in Montreal as it would in Jewish immigrant communities worldwide.The same visitor returning in the mid-1920s would fi nd the city profoundly transformed on many levels.A Jewish population numbering in the tens of thousands had become fi rmly entrenched in the city, concentrated in an immigrant quarter that stretched along Boulevard St-Laurent (St Lawrence Boulevard) and east of Mount Royal Park.The Jewish vernacular of Yiddish had become the most widely spoken language in the province after French and English.The Jewish community had created a comprehensive and cohesive Yiddish milieu, with an infrastructure that included newspapers, schools, libraries, literary life, and theatre and spanning an ideological spectrum ranging from the secular left wing through the most religiously xiv P r e fac e
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.560 | 0.392 |
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".