Racialized experiences as in-betweenness in academia
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
This article draws on an in-depth narrative of a Chinese woman, early career researcher based in a UK business school, to consider questions of subtle racism in academia. Specifically, engaging with our informant’s testimony, and reading it in the context of critical organizational debates on race, we offer episodic accounts of the subtle racism that she has encountered in academia to conceptualize experiences of in-betweenness of racial minorities excluded from dominant diversity discourses. In her case, subtle racism appears to emanate from a set of gendered and racialized tropes, culminating in the “model minority” myth. This article captures how racism is encountered differently by different populations; specifically, it illuminates how racism materializes in culturally-dependent, idiosyncratic forms, which should not be de-contextualized from the historical, political, and social dynamics that engender it. In so doing, it contributes to recent efforts to speak out against racism in the academy.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.005 | 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