Bibliographic record
Abstract
Bernina blata was sentenced to death in Illinois in 1999 for being a lesbian--or, as the prosecutor labeled her, a "hard core lesbian." Such a declaration strains credibility. 1999? Illin6is? Sentenced to death? Is this really a claim of a direct causal link? In my previous scholarship investigating lesbians and the crimi-nal justice system, I interrogated the prosecutorial use of lesbianism in trials and sentencing and often, not surprisingly, discovered bias against lesbians (Robson, p. 1998). Nevertheless, I concluded that I could not sustain any claim of legal causation and argued that posit-ing lesbianism (and other identities) "as the cause of prosecution and conviction is facile, " and it was more important to consider statistical overrepresentation and the tropes which prosecutors use to dehumanize the lesbian defendant (ibid., p. 46-47). Analyzing the transcripts of two lesbians who were then on death row-Aileen tt'uronos, who has since been executed, and Ana Cardona, who has
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".