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Record W4403465827 · doi:10.35844/001c.123401

Navigating Ethical Tensions Through Critical Reflexivity: A Participatory Filmmaking Research Project With Children With Disabilities

2024· article· en· W4403465827 on OpenAlexaff
Tanya Elizabeth Benjamin‐Thomas, Debbie Laliberté Rudman, Jeshuran Gunaseelan

Bibliographic record

VenueJournal of Participatory Research Methods · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsWestern University
Fundersnot available
KeywordsFilmmakingReflexivityCitizen journalismParticipatory action researchSociologyPhotovoicePsychologyEngineering ethicsPolitical scienceSocial scienceVisual artsArtEngineeringAnthropology

Abstract

fetched live from OpenAlex

This paper illustrates the importance of critical reflexivity in guiding socially and ethically responsible participatory research through an analysis of reflexive notes pertaining to the process of a participatory filmmaking research project with children with disabilities. Within this process, numerous ethical tensions emerged in the field regarding the participation of children with disabilities, authenticity of stories shared, navigating facilitator’s voice, issues of representation of child co-researchers, safety and risks associated with sharing everyday realities within the film, and limits to immediate action. The practice of individual and shared critical reflexivity among researchers, and inclusivity of child co-researchers, was central in navigating ethical tensions. This paper makes transparent the process of critical reflexivity within a participatory action research project by highlighting the ethical tensions faced, contextualizing them within cultural practices and power relations, and sharing strategies used to address ‘ethics in practice.’ We end by proposing practical strategies to enhance reflexive research practices in participatory work.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
grokMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativehigh
opusMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.216
metaresearch head score (Gemma)0.127
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2160.127
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0040.016
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.016
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 head0.955
GPT teacher head0.816
Teacher spread0.139 · 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

Labeled directly by 3 models reading the full record.

Study designQualitative
DomainMethods
GenreMethods · Empirical

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

Citations3
Published2024
Admission routes1
Has abstractyes

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