Generation X leaders from London, New York and Toronto
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
Inspired by scholarly calls to focus more intently on the influence of context on leaders’ construction and negotiation of identity, this paper draws on evidence from our Economic and Social Research Council (ESRC) project in London, New York City and Toronto. Throughout the paper, we strive to illuminate how the city-based context influences how race/ethnicity is experienced and described. We use social identity theory, organisational fit and in-group prototypes to frame school leaders’ explicit discuss race/ethnicity when reflecting on identity. We describe our data gathering process using our Professional Identity card-sort Tool, which guided leaders’ reflections on identity. The analysis details how we extracted and interpreted evidence from leaders who were explicit about the interrelationship between their own personal racial/ethnic identification and its alignment or misalignment with their school-level communities. We explore how different city contexts influence leader experience of in-groups and out-groups and the related leadership challenges and opportunities. In conclusion, we reflect on the influence that structures, policies and communities have on how leaders experience identity and the possible implications for their work. We also explore the value of attending to potential context-based identity-driven experiences for school leader development and support.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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