‘Why does she have dark skin?’: the ways Black women early childhood educators engage in intersectional pedagogies
Bibliographic record
Abstract
Based on a larger study, this paper highlights the lived-experiences and counter-stories of nine Black early childhood educators (ECEs). We explore how Black women’s positionality shapes their action, advocacy, and engagement with children, families, and the wider ECEC community through their intersectional pedagogy. We work with the original meaning of intersectionality, by focusing on the race–gender dimension of Black women, and employ Black feminist thought and critical race theory, to ask: What are the ways the practices of Black Women ECEs take up intersectional pedagogy? The findings centre on three key themes: (1) self as an entry point, (2) practices of othermothering as tradition y that drive the intervention strategies of Black women ECEs in supporting the flourishing of Black children and families, and (3) embodied knowledge and intersectional practices. We highlight that Black feminist pedagogy is a unique type of intersectional pedagogy that is culturally relevant and engaged with othermothering practices.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".