Bibliographic record
Abstract
Representing Rape is the first feminist analysis of the language of sexual assault trials from the perspective of linguists. Susan Ehrlich argues that language is central to all legal settings - specifically sexual harassment and acquaintance rape hearings where linguistic descriptions of the events are often the only type of evidence available. Language does not simply reflect but helps to construct the character of the people and events under investigation. The book is based around a case study of the trial of a male student accused of two instances of sexual assault in two different settings: a university tribunal and a criminal trial. This case is situated within international studies on rape trials and is relevant to the legal systems of the US, Canada, Britain, Australia, and New Zealand. She shows how culturally-dominant notions about rape percolate through the talk of sexual assault cases in a variety of settings and ultimately shape their outcome. Ehrlich hopes that to understand rape trials in this way is to recognize their capacity for change. By highlighting the underlying preconceptions and prejudices in the language of courtrooms today, this important book paves the way towards a fairer judicial system for the 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".