Sexual rights and sexual pleasure: Sustainable Development Goals and the omitted dimensions of the <i>leave no one behind</i> sexual health agenda
Bibliographic record
Abstract
This commentary explores the missing discourse of sexual rights and sexual pleasure in the Sustainable Development Goals (SDG) that purport to leave no one behind. The SDG propose a welcome focus on sexual health and human rights for all, expanding beyond the Millennium Development Goals. While promising in many ways for advancing global sexual and reproductive health, and reproductive rights, the omission of sexual rights is troubling. So too is the erasure of lesbian, gay, bisexual, transgender and queer (LGBTQ) persons, and sex workers, from the SDG discussions of social inequities. Illustrative examples are provided to demonstrate how a sexual rights focus could advance SDG 3 focused on healthy lives and well-being for all. First, sexual rights are presented as integral to realizing Target 3.3’s focus on ending the HIV pandemic among LGBTQ persons and sex workers (and LGBTQ sex workers). Second, sexual pleasure is introduced as an integral component of sexual health and sexual rights that could facilitate the realization of Target 3.7’s aim to provide universal access to sexual and reproductive health information and education. To truly leave no one behind and realize sexual health for all, the SDG need to begin from a foundation of sexual rights.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.038 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.014 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 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".