Catch Me When I Fall! Resiliency, Freedom and Black Sisterhood in the Academy
Bibliographic record
Abstract
Many Black women academics feel caged in their ‘subject position[s]’ within the academy. They are challenged by lack of opportunities and mentorship, isolation, explicit racism, micro-aggressions and stereotyping. Despite the ways in which their bodies are marked by racist sexism, Black women faculty take on an inordinate amount of unrecognized, differentiated labour and service work in the academy. They tend to assist other racialized colleagues, graduate and undergraduate students to achieve academic success. There is a common thread of resiliency among these women who successfully navigate their paths in the academy through applications of the concept of Radical Black Academic Sisterhood. This is an interpretive praxis that utilizes both an oppositional stance and creates brave spaces to deal with experiences of being caged.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.022 | 0.026 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".