Aligning the ontologies of leadership and coaching using Leadership-as-Practice
Bibliographic record
Abstract
The racial reckoning that occurred after the murder of George Floyd and the remote workplace dynamics created by the pandemic contributed to the tension that many Black professionals felt.Despite the efforts to maintain professionalism and collegiality, organisations did little to assuage the racial reckoning beyond pledges to initiate social justice and racial equity organisational change.This paper aims to help build a body of literature that acknowledges the unique vantage point of those with overlapping marginalised identities and, in particular, we examine the ways in which seven Black women leadership coaches understood and navigated workplace tensions after the racial reckoning.Through their coaching, these leadership coaches were able to help Black leaders build their capacities and improve their performance.Using armouring, they were also able to facilitate conversations about race within their organisations toward developing policies and practices that would help them move toward racial equity.
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 | 0.018 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.008 | 0.053 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".