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Record W3009582339 · doi:10.1177/1476750320905900

Using photovoice to reflect on poverty and address social inequalities among primary care teams

2020· article· en· W3009582339 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAction Research · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsMcGill UniversityUniversité du Québec en OutaouaisUniversité LavalUniversité de Sherbrooke
FundersInstitute of Health Services and Policy Research
KeywordsPhotovoiceParticipatory action researchPovertyTransformative learningGeneral partnershipContext (archaeology)Action researchHealth careSociologyPublic relationsNursingPolitical scienceEconomic growthMedicinePedagogy

Abstract

fetched live from OpenAlex

A participatory action research project using photovoice was developed in partnership with an international community organization working to overcome poverty. Twenty-eight healthcare professionals and persons in poverty participated in the study. The project consisted of several discussion sessions, creation of a photo exhibition, and knowledge transfer to the community and healthcare system. Photovoice proved to be a transformative method, generating benefits for academic and non-academic researchers, while leading to changes in primary care settings, such as integration of patient socio-economic context in electronic medical records and removal of administrative fees for patients on social assistance.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.917
GPT teacher head0.734
Teacher spread0.184 · 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