Bibliographic record
Abstract
This article addresses the implications of a new resistance to hate crime legislation that has yet to be addressed in the mainstream legal debate in Canada or the United States. It comes mainly from groups in the US that represent lgbtq communities who are poor and/or of color. These communities are particularly vulnerable to victimization by hate crime yet the groups have repeatedly opposed the inclusion of sexual orientation and gender identity/expression in hate crime legislation. This article addresses the underlying rationale of the new resistance and its implications for the mainstream debate. It begins by undertaking a comparative analysis of hate crime legislation in Canada and the US. It then considers the mainstream legal debate in both countries as well as some statistical data on hate crime. The third section turns to the new resistance as well as emerging data on the connection between victimization and the criminal legal system itself. It then draws on the legal theory of Walter Benjamin to reveal limits in the way that the mainstream legal debate conceptualizes criminalization. The final section of the article considers the implications of Benjamin’s concept of law for both the mainstream debate and the new resistance.
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 | 0.018 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.014 | 0.146 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.011 |
| 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".