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Record W3147741236 · doi:10.1080/01900692.2021.1903500

A COMPASS for Navigating Relationships in Co-Production Processes Involving Vulnerable Populations

2021· article· en· W3147741236 on OpenAlex
Gillian Mulvale, Ashleigh Miatello, Jenn Green, Maxwell Tran, Christina Roussakis, Alison Mulvale

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Public Administration · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCanadian Mental Health AssociationUniversity of TorontoMcMaster University
Fundersnot available
KeywordsVulnerability (computing)StakeholderCompassProduction (economics)Power (physics)Mental healthPsychologySociologyPublic relationsPolitical scienceComputer scienceGeographyCartographyComputer securityPsychotherapist

Abstract

fetched live from OpenAlex

When it comes to engaging vulnerable populations in co-production, power imbalances across stakeholder groups can create methodological challenges. A thoughtful, planned, and responsive approach is needed to prepare vulnerable participants to fully engage in co-production processes. Data from key informant interviews (n = 16) and author reflections on three Experience-based co-design (EBCD) studies involving youth (16–25 years) with mental health issues in Ontario Canada, were analyzed. Four overarching themes and 12 subthemes were identified, and heuristic tools (a relational COMPASS and MAPS directions) were developed to assist researchers in navigating vulnerability, power and relational issues in co-production processes involving vulnerable populations.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.501
GPT teacher head0.524
Teacher spread0.023 · 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