Identifying structural barriers to an effective HIV response: using the National Composite Policy Index data to evaluate the human rights, legal and policy environment
Bibliographic record
Abstract
INTRODUCTION: Attention to the negative effects of structural barriers on HIV efforts is increasing. Reviewing national legal and policy environments with attention to the international human rights commitments of states is a means of assessing and providing focus for addressing these barriers to effective HIV responses. METHODS: Law and policy data from the 171 countries reporting under the Declaration of Commitment from the 2001 United Nations General Assembly Special Session on HIV/AIDS were analyzed to assess attention to human rights in national legal and policy environments as relevant to the health and rights of key populations such as people who inject drugs, men who have sex with men and sex workers. RESULTS: Seventy-eight governments and civil society in 106 countries report the existence of laws and policies which present obstacles to accessing HIV services for key populations. Laws and policies which positively affect access to HIV-related services, in and of themselves constituting structural interventions, were also reported. The dissonance between laws and how this impacts the availability and use of HIV-related services deserve greater attention. CONCLUSIONS: Recognition of the harms inherent in laws that constitute structural barriers to effective HIV responses and the potential positive role that a supportive legal environment can play suggests the need for legal reform to ensure an enabling regulatory framework within which HIV services can be effectively delivered and used by the populations who need them. Moving beyond laws and policies, further efforts are required to determine how to capture information on the range of structural barriers. Teasing apart the impact of different barriers, as well as the structural interventions put in place to address them, remains complicated. Capturing the impact of policy and legal interventions can ultimately support governments and civil society to ensure the human rights of key populations are protected in national HIV responses.
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 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".