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Record W2251085002 · doi:10.1353/cpr.2015.0079

“Hear(ing) New Voices”: Peer Reflections from Community-Based Survey Development with Women Living with HIV

2015· article· en· W2251085002 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProgress in community health partnerships · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsHuman immunodeficiency virus (HIV)Gender studiesCommunity-based participatory researchSociologyPeer reviewGerontologyPsychologyPolitical scienceMedicineParticipatory action researchFamily medicineAnthropology

Abstract

fetched live from OpenAlex

BACKGROUND: The Canadian HIV Women's Sexual and Reproductive Health Cohort Study (CHIWOS) engaged in an innovative community-based survey development process. OBJECTIVES: We sought to provide 1) an overview of the survey development process, and 2) personal reflections from women living with human immunodeficiency virus (HIV; "peers") on their own observations of strengths and short-comings of the process and opportunities for improvement. METHODS: Guided by the principles of community-based research (CBR) and meaningful involvement of women living with HIV (WLWH), CHIWOS coordinated a national, multidisciplinary research team, and facilitated a community based survey development process. LESSONS LEARNED: Four key lessons emerged highlighting the importance of 1) accommodating different preferences for feedback collection, 2) finding the right combination of people and skills, 3) formalizing mentorship, and 4) creating guidelines on survey item reduction and managing expectations from the outset. CONCLUSIONS: Peers discussed the strengths and weaknesses of participatory methodologies in survey development.

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.

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)0.168
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.703
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1680.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.690
GPT teacher head0.535
Teacher spread0.156 · 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