Bibliographic record
Abstract
Why do states regulate sexuality?This is the question Julian C.H. Lee asks at the beginning of this wide ranging discussion of the legal and social regulation of sex and sexuality by the state.Using case studies from countries as diverse as Malaysia, Turkey and the UK, Lee provides an introduction to sexuality and its regulation which should be accessible even to laypeople and does certainly provide some interesting insights even to those with an academic background in law, politics or sexuality.In its intention to illustrate the regulation of sexuality with case studies from different countries this book is comparable to Rosie Harding's recent book Regulating Sexuality: Legal consciousness in lesbian and gay lives (2010) which explores some of the more recent legal reforms affecting Lesbian, Gay, Bisexual, Transgender, Intersex and Questioning (LGBTIQ) people in Britain, the US and Canada.However Lee's book distinguishes itself by including women's rights in his analysis of sexuality and also considering a much wider range of countries and issues.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".