Bibliographic record
Abstract
The trend of managerialism and neo-liberalism sweeping across universities demands peer-reviewed outcomes, which replace discourses of ‘service.’ Within this context I, a racialized immigrant faculty member from the global South, ventured on a journey as an Associate Director, Student Affairs. I realized that I needed to take a detour, as my commitment to service was competing with the expectation of meeting the ever-growing number of peer-reviewed outcomes. The situation reminded me of my previous experiences with the university administration around ‘service.’ Based on my subjectivities I had no choice other than to ‘comply’ with the discourse of managerialism and neo-liberalism. I gave up ‘service’ as an academic administrator to pursue research and publication. My decision raises questions about the fairness of similar compliance by other racialized, new immigrant academics. Using critical auto-ethnography, I challenge the current managerial and neo-liberal
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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.036 | 0.065 |
| Scholarly communication | 0.025 | 0.025 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".