Exploring anti-racism within the context of human resource management in the health sector in Aotearoa
Bibliographic record
Abstract
Compelling evidence continues to demonstrate that racism is a modifiable determinant of health inequities. Despite growing recognition of this it is less clear how from a human resource perspective to engage in effective anti-racism.
 
 Through a review of human resource and anti-racism literature, the white, Indigenous and racialised authors examined existing approaches to anti-racism applicable to the health system in Aotearoa.
 
 Two systemic organisational approaches were identified: diversity training and dismantling institutional racism. Recruitment processes, talent management and retention were human resource specific sites for interventions. Insights from anti-racism scholarship including upholding te Tiriti o Waitangi and engaging in decolonising to enable transformative change.
 
 Power-sharing remains at the heart of anti-racism praxis. A health sector response needs to be co-created with Māori and those with the political will to enable transformation. Given racism has a geographic specificity, solutions need to be informed by the cultural, political, social, and historical context.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".