Mapping Work in Early Twentieth-Century Montreal: A Rabbi, a Neighbourhood, and a Community
Bibliographic record
Abstract
Rabbi Simon Glazer’s 1909 daily journal provides a window onto his role as an orthodox rabbi of a largely Yiddish-speaking immigrant community, his interactions with Jewish newcomers, the range of tasks he performed to augment the inadequate stipends he received from a consortium of five city synagogues where he was chief rabbi, and the ways in which Jewish newcomers sought to become economically independent. Using a multidisciplinary methodology, including Historical Geographic Information Systems (HGIS), Glazer’s journal offers a new lens through which to view and map the social geography of this community. Our study contributes to a growing body of literature on immigrant settlement, which has shown that such clustering encouraged economic independence and social mobility. Characterized by a high degree of diversity in ethnicity and commerce, the St. Lawrence Boulevard corridor was an ideal location for Jewish newcomers to set down roots. We argue that the community served as a springboard for social mobility and that Simon Glazer played an important role at a critical moment in its early development. It was on its way to becoming one of Canada’s most significant Jewish communities. Over the eleven years that he worked in Montreal (1907–18), Glazer carved out a vital place for himself in the city’s Jewish immigrant community and honed skills that would serve him well when he returned to the United States.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".