An implementation evaluation of the Breaking Down human rights barriers to HIV services initiative in Ukraine
Bibliographic record
Abstract
INTRODUCTION: Globally, stark inequities exist in access to HIV treatment and prevention. The eastern European and central Asian region is experiencing the sharpest rise in new HIV acquisition and deaths in the world, with low rates of treatment and prevention services, especially for key and vulnerable populations who face a range of human rights-related barriers to HIV prevention and treatment. METHODS: An implementation learning evaluation approach was used to examine the implementation of the Breaking Down Barriers initiative targeting key and vulnerable populations in Ukraine. Between September 2022 and April 2023, researchers conducted 23 key informant interviews with individuals from the Ukrainian government, implementing organizations and human rights experts. Using a concurrent triangulation design, researchers and key informants, in a process of co-creation, sought to describe programme accomplishments, challenges and innovations in implementation, between 2021 and 2023, including periods before and after Russia's February 2022 full-scale invasion. RESULTS: Eight rights-based interventions related to HIV were identified in Global Fund programme documents and key informant interviews as making up the core of the Breaking Down Barriers initiative in Ukraine. These included programmes seeking to: eliminate stigma and discrimination; ensure the non-discriminatory provision of medical care; promote rights-based law enforcement practices; expand legal literacy ("know your rights"); increase access to justice; improve laws, regulations and policies; reduce gender discrimination, harmful gender norms and violence against women and girls; and mobilize communities for advocacy. These programmes received US$5.9 million in funding. Key informants reported that significant progress had been made addressing human rights barriers and scaling up interventions, both before and after Russia's invasion. Programme implementors adopted innovative approaches, including using paralegals, hotlines and other community-led interventions, to ensure that key and vulnerable populations, including displaced individuals, were able to access prevention and care. CONCLUSIONS: An implementation learning evaluation approach examining programmes addressing human rights barriers to HIV services, designed as a process of co-creation between researchers, programme implementors, government officials and human rights experts, can provide a robust assessment of programme outputs, outcomes and evidence of impact, despite a challenging operational environment.
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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 | 0.030 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".