Race and educational leadership: The influence of research methods and critical theorising in understanding representation, roles and ethnic disparities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The special issue offers new knowledge about racialised educational experiences by shedding light on racialised leadership in school and higher education in diverse geographical and educational contexts in England, Canada, America and South Africa through a mix of research methods (phenomenological, longitudinal, documentary, semi-structured interviews), analytical (content and textual analysis) and theoretical approaches (critical race theory [CRT], critical ecological). This special issue prioritises the centring of educational leaders’ lived experiences and their voices alongside the research methods used to illuminate the nuances associated with race and educational leadership in schools and higher education. The prism of race enables us to add new educational leadership insights to the field associated with ethnicity, gender, culturally constructed notions of leadership, intersectionality and/or geographical location. The findings highlight implications for researching race and educational leadership.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it