DOING GENDER AND RACE INTERSECTIONALITY: THE EXPERIENCES OF FEMALE MAORI AND NONWHITE ACADEMICS IN NEW ZEALAND
Bibliographic record
Abstract
Several studies that focus on Western settings like Canada, the United States, the United Kingdom, Australia, and New Zealand have found that gendered institutions within academic careers are still preserved through various means. These studies have verified that fewer women are in tenure track positions than men. Additionally, women have been receiving a lower salary and are seldom promoted. Several issues such as mobility, parenting, and gender bias in application and evaluation rate as well as gender citation gap are highly correlated with women’s challenges in pursuing professorships. Nonetheless, there is still a lack of studies pertaining to the impact of the intersection of race and gender on the experiences of people of colour and minority groups in academia. The current study aims to explore the role that gender and race play among female academics, which includes the careers of Maori academics (the indigenous people of New Zealand) and non-white academics in New Zealand. Based on in-depth interviews conducted with 15 academic staff, including Maori and non-white academics in New Zealand, the current research corroborates the existing literature regarding the interplay of race and gender in advancing academic career. Furthermore, this research also finds that the merit-based concept or objective indicators of academic excellence do not necessarily apply in New Zealand. On account of their gender and racial identities, women of minority groups and non-white academics frequently experience multidimensional marginalisation while pursuing their academic careers.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".