Mapping Blackness in the Stacks: A Conversation with Dr. Dorothy Williams
Bibliographic record
Abstract
Dr. Dorothy W. Williams is a prize-winning independent historian, archivist, and memory worker of Black Canada. She has published two monographs on Montreal’s Black community and has done extensive research on the history of Black print in Quebec during the 20th century — amongst other topics. Her research and public history efforts cannot, however, be dissociated from her decades-long collecting and archiving work — the focus of this edited interview. Over the years, she amassed an extensive archival collection of Black Montreal in her home and worked to preserve the archives of many Black institutions in the city. Following a bio-bibliographical approach, the interview examines the evolution of her collecting practices and their reciprocal relation with her scholarship and pedagogy.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.058 | 0.026 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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".