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Record W4220776441 · doi:10.1177/10497323221089877

The Ethics of Financial Incentivization for Health Research Participation Among Sex Workers in a Canadian Context

2022· article· en· W4220776441 on OpenAlexafffundabout
Vicky Bungay, Adrian Guţă, Allie Slemon, Colleen Varcoe, Scott Comber

Bibliographic record

VenueQualitative Health Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsDalhousie UniversityUniversity of WindsorUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsIncentivePaternalismThematic analysisRedressTransactional sexContext (archaeology)OppressionHarmAutonomyQualitative researchPublic relationsBeneficenceSocial psychologyPolitical sciencePsychologySociologyMedicinePoliticsEconomicsSocial scienceLawEnvironmental health

Abstract

fetched live from OpenAlex

Research incentivization with sex workers is common, yet limited guidance exists for ethical incentives practice. We undertook a critical qualitative inquiry into how researchers ( n = 17), community services staff ( n = 17), and sex workers participating in research ( n = 53) perceive incentives in a Canadian context. We employed an interpretive thematic approach informed by critical perspectives of relational autonomy for analysis. Four themes illustrate how (un)ethical use of incentives is situated in transactional micro-economies among groups experiencing severe marginalization: i) transactional research economy , ii) incentive type: assumptions and effects, iii) incentive amount: too much too little? , and iv) resistance, trauma, and research-related harm . Paternalistic assumptions about capacities of sex workers to act in their own best interests conflicted with participants’ rights and abilities for self-determination; with researchers maintaining ultimate decision-making authority. Power differentials create conditions of harm. Safe, equitable approaches concerning research incentive use must redress relations of power that perpetuate oppression.

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)0.170
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1700.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0100.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.575
GPT teacher head0.663
Teacher spread0.088 · 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; both teacher heads agree on what is shown here.

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
Published2022
Admission routes3
Has abstractyes

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