Bibliographic record
Abstract
Black girls take up a unique space in society. To authentically capture the experiences of Black girlhood in the 21st century means to combine how concepts of race, ethnicity, gender, sexuality, class, religion, disability, and nationality inform or affect identities of Black girls within educational settings and beyond. But what is the Black girl code and how does it relate to keeping feminism relevant? Black Canadian feminism encompasses several aspects of one’s identity. As we read the stories of stereotypes and expectations of Black girls, we realize that the outdated definition of feminisms prioritized social conformity over individual identity, as well as community solidarity. In 2010 there was a positive shift, and the idea of feminism became more well-rounded showing more inclusive identities including the Girl Boss and more diverse personalities. In 2023 we see the importance of prioritizing female friendships rather than vying for the male gaze. Due to long-standing oppressive systems of White, hegemonic, masculinity as the default of systems, Black Canadian feminism can be a useful framework to address gender-based violence, sexual assault, and a lack of abortion access among other things in these current times.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.076 | 0.015 |
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".