As sunflowers face the sun: exploring the experiences of Black and Indigenous women educational leaders
Bibliographic record
Abstract
Currently, the field of educational leadership continues to exclude the crucial voices of historically marginalized school administrators. As such, this study sought to learn more about the experiences of Black and Indigenous women educational leaders. To contribute to the scant literature available the authors ethically and intentionally recruited participants who self-identified as women, Black, Indigenous or Afro-Indigenous. The data collection for this qualitative study included individual interviews with 15 participants that were then analyzed and coded on NVivo in accordance with Black feminist thought, Indigenous feminisms critical race theory in education, specifically, the tenets of intersectionality and counter-storytelling. Findings from the study suggest that Black and Indigenous women school administrators have much in common in their approach to leadership. For instance, the collective ways in which they engage in the world, and how they define healing and their collective need for it. Finally, this study serves as an opening space for Black and Indigenous women school leaders not only share their lived experiences, but to address cross-identity solidarity that is specific to Black and Indigenous peoples.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".