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Record W1536888178 · doi:10.1177/160940690900800203

Using PAR or Abusing its Good Name? the Challenges and Surprises of Photovoice and Film in a Study of Chronic Illness

2009· article· en· W1536888178 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.

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhotovoiceIntervention (counseling)Action (physics)Quality of life (healthcare)Participatory action researchMedicinePsychologyCitizen journalismNursingSociologyGerontologyPolitical scienceVisual artsLaw

Abstract

fetched live from OpenAlex

Without dispute, kidney dialysis treatment has been successful in saving lives. As a result of this intervention, increasing numbers of people are now facing the many physical, social, and emotional challenges of living with ESRD (end stage renal disease). Compromised vision, mobility, dexterity, and overall health have presented important methodological challenges to the authors' participatory action research (PAR) study of ESRD patients' quality of life. This article proceeds broadly in three steps: (a) an explanation of the authors' interest in PAR and the challenges that ESRD poses for PAR, (b) a description of how they adapted two visual techniques (photovoice and documentary film making) to address those challenges, and (c) a discussion of how they have and have not overcome the challenges of working with PAR.

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)0.033
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.934
GPT teacher head0.777
Teacher spread0.157 · 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