Bibliographic record
Abstract
“Fugitive libraries,” as described by Shannon Mattern in her titular work, are Black libraries that emerge in American contexts in response to conditions of exclusion and antiBlackness. The question of whether they are necessary in a Canadian cultural context has not been investigated before, in part due to the lack of distinct existing scholarship on Black Canadian librarianship. Using an interdisciplinary framework informed by Black Canadian and Indigenous scholars, I undertake a content analysis and close reading of Black History Month and Black Lives Matter programming and booklists in two Canadian public libraries from 2020-2021 to investigate whether the programming meets the needs of Black Canadian communities, and whether fugitive libraries are a necessary response. I determine that though clear efforts towards the inclusion of Black narratives are apparent in these libraries, Black History Month programming and the discourse surrounding it are shaped to benefit and mobilize non-Black Canadians, rather than to address the needs of particular Black communities, and propose fugitivity as a solution to these conditions.
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.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.035 | 0.040 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".