The language of sexual violence and impropriety
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In Canada, which has two official languages, sexual violence and impropriety have been identified as problems in the military for at least 25 years (see Duval-Lantoine 2022 ). In the military’s efforts to address these problems, the institutional language has been identified as problematic ( Deschamps 2015 ; Arbour 2022 ). This paper addresses the labels for sexual violence and impropriety in Canadian English and French using large corpora of language data: the Corpus of Historical American English, the Corpus of Contemporary Amerian English, the enTenTen20 corpus, the frTenTen20 corpus, the Strathy Corpus, and the Canadian Hansard. Findings show differences between the most widely used labels in American and Canadian data and between English and French. This raises questions about the labels adopted by the Canadian military and the extent to which sexual violence and impropriety can be addressed without a critical review of the language in use.
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.
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 | 0.001 | 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) | 0.000 | 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 it