MétaCan
Menu
Back to cohort
Record W2945253389 · doi:10.34880/6rsn-bh35

Making Harm Reduction Work for Women: The Ukrainian Experience

2021· article· en· W2945253389 on OpenAlexaboutno aff
Sophie Pinkham, Anna Shapoval

Bibliographic record

VenueOpen Society Foundations · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsUkrainianWork (physics)Harm reductionHarmPolitical scienceReduction (mathematics)MedicineLawEngineeringPublic health

Abstract

fetched live from OpenAlex

Ukraine‘s adult HIV prevalence is the highest of any country in Europe or Central Asia. According to the United Nations Development Programme, women now account for 48 percent of all HIV cases among adults in the country. Regional analysis suggests that this increase is largely attributable, either directly or indirectly, to injection drug use. UNAIDS estimates that 35 percent of women living with HIV in Eastern Europe and Central Asia acquired the virus through injection drug use, and a further 50 percent were infected through unsafe sex with partners who inject drugs. Ukrainian programs have made great strides in responding to the HIV epidemic among injection drug users by introducing syringe exchange programs, methadone and buprenorphine treatment, anti-AIDS treatment, and programs to prevent mother-to-child transmission of HIV. Yet, these programs have rarely succeeded in fully accounting for the needs of women drug users. In response to the existing gap in harm reduction services for women who use drugs, the Open Society International Harm Reduction Development Program, with the support of the Canadian International Development Agency, gave grants to six Ukrainian harm reduction organizations to implement gender-responsive services. Rather than developing new, separate programs for women, the grants were designed to build on the existing work of the organizations. This report documents the experiences of the six programs, and offers recommendations for developing an effective system of care for women who use drugs.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.184
GPT teacher head0.434
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOpen Society FoundationsSame topicGender, Security, and ConflictFrench-language works237,207