Sex, Love, and Marriage: Questioning Gender and Sexuality Rights in International Law
Bibliographic record
Abstract
The cover of Sex Rights: The Oxford Amnesty Lectures 2002 shows a picture of two men photographed from the back, with their hands holding each other's waists. They are walking towards a camera crew. Based on the way they are dressed, it seems that they have just been married. Both men are wearing white dress shirts and have similar hairstyles, with one wearing a black waistcoat over the white shirt and the other with black braces. This collection, based on the Oxford Amnesty Lectures series on gender and sexuality, thus apparently features on its cover the same-sex marriage of two men, ostensibly held in one of the few jurisdictions that have legalized such a union (perhaps the Netherlands, which was the first to do so, and was later followed by Belgium, Spain, Canada, Massachusetts (United States), and South Africa). And while we know that ‘love and marriage go together like a horse and carriage’, what has sex got to do with this? Would it not be more appropriate for a cover of a book entitled Sex Rights to feature two persons engaged in sex or having just engaged in sex rather than a marriage ceremony? Would it not be more appropriate to depict, on a cover of a book called Sex Rights, a picture of two men in a position that suggests they have just had sex, an act for which they could be persecuted and prosecuted in various jurisdictions? So why, then, does a book on Sex Rights feature same-sex marriage on its cover?
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.054 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".