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Record W2362781966 · doi:10.1093/phe/phw024

Governing<i>Well</i>in Community-Based Research: Lessons from Canada’s HIV Research Sector on Ethics, Publics and the Care of the Self: Table 1.

2016· article· en· W2362781966 on OpenAlexafffundabout
Adrian Guţă, Stuart J. Murray, Carol Strıke, Sarah Flicker, Ross Upshur, Ted Myers

Bibliographic record

VenuePublic Health Ethics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsYork UniversityCarleton UniversityUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsSociologyResearch ethicsPublic relationsCognitive reframingMoralityEngineering ethicsPsychologySocial psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this paper, we extend Michel Foucault's final works on the 'care of the self' to an empirical examination of research practice in community-based research (CBR). We use Foucault's 'morality of behaviors' to analyze interview data from a national sample of Canadian CBR practitioners working with communities affected by HIV. Despite claims in the literature that ethics review is overly burdensome for non-traditional forms of research, our findings suggest that many researchers using CBR have an ambivalent but ultimately productive relationship with institutional research ethics review requirements. They understand and use prescribed codes, but adapt them in practice to account for the needs of participating community members, members of their research teams and the larger communities with whom they work. Complying with ethics protocols was seen as only the beginning, a minimum standard; our research suggests that the real ethical work happens in the field, where CBR practitioners encounter community members in diverse public roles and must forge ethical consensus across communities. CBR represents an ethical terrain in which practitioners challenge themselves to work differently, and as a result they care for themselves-and others-in ways that often resist the propensity for domination through public health research. '…there are different ways to "conduct oneself" morally, different ways for the acting individual to operate, not just as an agent, but as an ethical subject of action.' (Foucault, 1985: 26).

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)0.070
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0700.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0500.084
Scholarly communication0.0340.012
Open science0.0050.013
Research integrity0.0090.016
Insufficient payload (model declined to judge)0.0040.000

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 head0.804
GPT teacher head0.561
Teacher spread0.243 · 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
DomainMethods
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

Citations6
Published2016
Admission routes3
Has abstractyes

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