Access to Information on Safe Abortion: A Harm Reduction and Human Rights Approach
Bibliographic record
Abstract
With convergence-divergence as an organizing theme, this Article explores harm reduction and human rights as conceptual approaches to and discourses about unsafe abortion. The vehicle for this exploration is access to safer-use information on medication abortion, namely women’s self-administration of the drug misoprostol. More specifically, this Article focuses on the Sanitary Initiative Against Unsafe Abortion (“the Uruguay Model”) as an actualized model or prototype of access to information through physician-patient consultation in restrictive legal environments.\nOn convergence, this Article seeks to test the claim that international human rights law imposes government obligations to provide, and to refrain from interfering with the communication of, information necessary to reduce the harms of unsafe abortion. Access to information is protected in international law through a constellation of human rights. These rights are articulated in broad terms, but given content and meaning through interpretation by courts, committees, Special Rapporteurs, and commissions. By reference to this jurisprudence, normative validation for harm reduction in unsafe abortion, and specifically access to safer-use information, is constructed from the human rights to life, health, and non-discrimination, among others.\nOn divergence, this Article seeks to make explicit the different moral warrants underlying harm reduction and human rights. Human rights are set against the normative neutrality of harm reduction, which is characterized by a pragmatic approach to health outcomes. The human rights shortcomings of access to safer-use information through physician-patient consultation, the Uruguay Model, are contrasted against a model driven by a feminist ideology, namely the Safe Abortion Hotline. The limitations of the pragmatic-neutrality of harm reduction in criminal law reform are set against a human rights approach, which envisions legal reform in service of broad social change.
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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 | 0.026 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.007 | 0.085 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".