Sankofa : recovering Montrealâs heterogeneous Black print serials
Bibliographic record
Abstract
Using the sankofa archival praxis, this thesis seeks to recover the unknown periodicals of Quebec’s largest urban area and Canada’s second largest. This qualitative research examines 196 Black periodicals published in Greater Montreal, from 1934 to the present. As a case study of Black-controlled serialized literature it includes: journals, newspapers, magazines, directories, bulletins, and newsletters. This thesis seeks to capture, organize, and catalogue a comprehensive checklist of Montreal’s Black serials. Despite the scores of Black publications produced in the last seventy years, the vast majority of the 196 titles located are unknown to Black readers within Montreal, Quebec. While this thesis assumes that the silence of these documents is intricately linked to the marginalized status of Blacks within Canada as a whole, and Quebec in particular, it focuses upon the context of the serials’ evolution, their concomitant invisibility within the Black community of Montreal and the national and urban context of these documents. The research does not ask why this body of literature is unknown to the general populace, but rather, why Blacks themselves, as creators, that is, the Black owners, journalists, and editors of the serials, are unaware of the existence of these serials. This dissertation explores the extent to which four factors may have contributed to the invisibility of these serials in Canada and in particular in the unique setting of Montreal: language, ethnicity, orality and the treatment of documents.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.021 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".