Little Burgundy: The Interwoven Histories of Race, Residence, and Work in Twentieth-Century Montreal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Until the 1950s, most black men in Montreal worked for the railway companies as sleeping car porters, dining car employees, and red caps. The city’s English-speaking black community took root in Little Burgundy because it was close to Windsor and Bonaventure train stations. The area between Saint-Henri and Griffintown, north of the Lachine Canal, in the city’s Southwest Borough, was once known by many names. “Little Burgundy” was invented in the 1960s by city officials to describe their urban renewal plans for the area. If employment mobility was foundational in making this community, it proved just as central in its unmaking in the 1960s and 1970s. The shift from trains to cars and trucks had a two-fold impact on Little Burgundy. First, employment levels collapsed with the decline of passenger train travel, leaving many black men unemployed. Then the state built a highway through the neighbourhood to facilitate the mobility of mainly white suburban workers and consumers making their way to the central city. Next, the neighbourhood was “renewed” on a massive scale. What followed were years of dislocation and crisis. Much of the black community was dispersed as a result. It was no coincidence. The radical restructuring of North American cities disproportionately affected racialized minorities and poor whites. What was different here was that the area’s reputation for being the birthplace of black Montreal emerged after the community had been largely dispersed by urban renewal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it