2021 Redux Survey of Visible Minority Librarians of Canada
Bibliographic record
Abstract
In 2021, the Visible Minority Librarians of Canada (ViMLoC) Network conducted its second comprehensive survey on visible minority librarians working in Canadian institutions. As a followup to the first 2013 survey, ViMLoC examined changes in the library landscape with regards to visible minority librarians in various librarian positions. Data were collected from January to March 2021 on visible minority librarians’ demographics, education, and employment situations. The survey was administered and distributed using Qualtrics in English and French. The user guide and results summary in this dataset presents aggregated data for 162 visible minority librarians from the English survey (138) and the French survey (24). Survey results will help ViMLoC identify the needs of visible minority librarians and propose projects to empower them in their current positions or their future career development. The data can be also useful to library administrators, librarians, and researchers working on multicultural issues, diversity, recruitment and retention, leadership, library management, and other related areas.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.021 |
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".