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‘It Looks Like You Just Want Them When Things Get Rough’: Civil Society Perspectives on Negative Trial Results and Stakeholder Engagement in<scp>HIV</scp>Prevention Trials

2012· article· en· W2126595916 on OpenAlexfundno aff
Jennifer Koen, Zaynab Essack, Catherine Slack, Graham Lindegger, Peter A. Newman

Bibliographic record

VenueDeveloping World Bioethics · 2012
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsStakeholderCivil societyStakeholder engagementCommunity engagementPublic relationsBioethicsStakeholder analysisPoliticsPolitical scienceHuman immunodeficiency virus (HIV)MicrobicideMedicineLaw

Abstract

fetched live from OpenAlex

Civil society organizations (CSOs) have significantly impacted on the politics of health research and the field of bioethics. In the global HIV epidemic, CSOs have served a pivotal stakeholder role. The dire need for development of new prevention technologies has raised critical challenges for the ethical engagement of community stakeholders in HIV research. This study explored the perspectives of CSO representatives involved in HIV prevention trials (HPTs) on the impact of premature trial closures on stakeholder engagement. Fourteen respondents from South African and international CSOs representing activist and advocacy groups, community mobilisation initiatives, and human and legal rights groups were purposively sampled based on involvement in HPTs. Interviews were conducted from February-May 2010. Descriptive analysis was undertaken across interviews and key themes were developed inductively. CSO representatives largely described positive outcomes of recent microbicide and HIV vaccine trial terminations, particularly in South Africa, which they attributed to improvements in stakeholder engagement. Ongoing challenges to community engagement included the need for principled justifications for selective stakeholder engagement at strategic time-points, as well as the need for legitimate alternatives to CABs as mechanisms for engagement. Key issues for CSOs in relation to research were also raised.

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)0.232
metaresearch head score (Gemma)0.220
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2320.220
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0320.076
Scholarly communication0.0200.015
Open science0.0030.018
Research integrity0.0150.023
Insufficient payload (model declined to judge)0.0030.000

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 head0.731
GPT teacher head0.537
Teacher spread0.194 · 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.

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

Citations22
Published2012
Admission routes1
Has abstractyes

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