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Record W4400831297 · doi:10.1002/jia2.26309

“…because the social work never ends”: a qualitative study exploring how NGOs responded to emerging needs while upholding responsibility to HIV prevention and treatment during the war in Ukraine

2024· article· en· W4400831297 on OpenAlexafffundabout
Lisa Lazarus, Leigh M. McClarty, Nicole Herpai, Daria Pavlova, Tatiana Tarasova, А. С. Гнатенко, Tetiana Bondar, Robert Lorway, Marissa Becker

Bibliographic record

VenueJournal of the International AIDS Society · 2024
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMedicineGeneral partnershipQualitative researchPopulationPublic relationsEconomic growthPolitical scienceSociologyEnvironmental healthSocial science

Abstract

fetched live from OpenAlex

INTRODUCTION: Since the onset of the Russian invasion on 24 February 2022, the health system in Ukraine has been placed under tremendous pressure, with damage to critical infrastructure, large losses of human resources, restricted mobility and significant supply chain interruptions. Based on a longstanding partnership between the Ukrainian Institute for Social Research after Oleksandr Yaremenko (UISR after O. Yaremenko) and the Institute for Global Public Health at the University of Manitoba, we explore the impact of the full-scale war on non-governmental organizations (NGOs, including charitable organizations) providing services for key population groups in Ukraine. METHODS: We conducted in-depth qualitative interviews with key representatives from NGOs working with key population groups (i.e., people living with HIV, sex workers, men who have sex with men, people who inject drugs and transgender people) throughout Ukraine. Members of the UISR after O. Yaremenko research team recruited participants from organizations working at national, regional and local levels. The research team members conducted 26 interviews (22 with women and four with men) between 15 May and 7 June 2023. Interviews were conducted virtually in Ukrainian and interpretively analysed to draw out key themes. RESULTS: Applying Roels et al.'s notion of "first responders", our findings explore how the full-scale war personally and organizationally impacted workers at Ukrainian NGOs. Despite the impacts to participants' physical and mental health, frontline workers continued to support HIV prevention and treatment while also responding to the need for humanitarian aid among their clients and the wider community. Furthermore, despite inadequate pay and compensation for their work, frontline workers assumed additional responsibilities, thereby exceeding their normal workload during the extraordinary conditions of war. CONCLUSIONS: NGOs play a vital role as responders, adapting their services to meet the emergent needs of communities during structural shocks, such as war. There is an urgent need to support NGOs with adequate resources for key population service delivery and to increase support for their important role in humanitarian aid.

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 imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0220.024
Scholarly communication0.0070.008
Open science0.0030.009
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.091
GPT teacher head0.413
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2024
Admission routes3
Has abstractyes

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