Bibliographic record
Abstract
We enter into an email exchange to discuss our research collaborations over the last 12 years, moving between Manila and Vancouver, and through relationships inflected by different power and imperial relations (graduate student–supervisor; new faculty–senior faculty; Filipino–white Canadian). Our email exchanges perform the intimacy of the epistolary genre of writing and we uncover the imperial histories that dog our collaborations, the work of emotional masking sometimes required of graduate student mentees, as well as the challenges of working in solidarity with grassroots organisations. We settle on accepting that collaborations are messy and that the capacity to bring conflict to the surface to work through is a necessary and helpful skill. Contemporary universities – despite talk of partnership and community engagement – are challenging spaces for feminist collaboration. We hold on to collaboration and co-authoring as ballast against the alienation of the individualizing competitive university.
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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.035 | 0.011 |
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".