Reply to Trask THE CONTEMPORARY PACIFIC · SPRING 1991
Bibliographic record
Abstract
Since Trask's vituperative commentary so strikingly exemplifies and hence reinforces many of the themes of my paper, my initial reaction was to decline to reply (other than, perhaps, to invite the reader to ponder which of us is a racist). However, I have been persuaded that some of the issues merit further debate and clarification. With regard to my own politics, in relation to issues of past colonial invasion (including missionary invasion), present neocolonialism and global capitalism, gender, and the struggles of Third and Fourth World peoples, I have been consistent, outspoken, and unequivocal in precept and practice. I feel no need to defend my track record on these issues (it is at least a change to be criticized for being too reactionary instead of for being too radical). The stark "insider " versus "outsider " dichotomy drawn in Trask's rhetoric troubles me for other reasons. It strikes me as a great leap backward in what purports to be radical discourse, a quarter century out of date. The time is long past where those who are friends of Pacific
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.020 | 0.037 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".