Bibliographic record
Abstract
This piece refers to a recurring dream about not being able to speak, not being able to be heard, and therefore, not being able to push back against threats of violence. I created it after having conversations with other Asian women about how we are constantly trying to speak out against systemic violence in organizations that claim to be anti-oppressive, and yet, are almost entirely made up of white folx at the managerial level. Our words momentarily capture attention – perhaps people are shocked at the assertiveness and articulateness of Asian women who are stereotyped as passive and politically apathetic – and we receive acknowledgement, apologies, and offers of help. But over time, we realize that not only has no meaningful change been made, but that we are now no longer invited to the table for discussions. The polite responses always drown out the calls for change, or the offers of help are conditional, requiring us to conform to a white middleclass standard of social respectability that erases our very ways of being and the agency of choice. At the same time, my conversations with friends remind me that we can still draw on each other for strengths, inspirations, and creative strategies to persist in our various spaces; to find small ways of resistance against what bell hook (1995) calls “white supremacist capitalist patriarchy” (p. 17); to continue to keep alive the dream of a less violent future.
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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.315 | 0.196 |
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".