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Record W2746603057 · doi:10.1386/jaah.8.2.141_1

Audience engagement and impact: Ethical considerations in art-based health research

2017· article· en· W2746603057 on OpenAlex
Marilys Guillemin, Susan Cox

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

VenueJournal of Applied Arts and Health · 2017
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConfidentialityVariety (cybernetics)Ethical issuesPoint (geometry)The artsEngineering ethicsPsychologyWork (physics)SociologyPublic relationsInternet privacyPolitical scienceComputer scienceEngineeringLaw

Abstract

fetched live from OpenAlex

Abstract Art-based research presents epistemological benefits and challenges for researchers and artists. There are also significant ethical implications for audiences as well as participants and researchers. We argue that it is important to consider who is in the audience and how to minimize potentially harmful effects of the work. This includes issues of privacy and confidentiality arising from incorporation of participants’ stories into the art form and the need to offer reassurance to audience members who may believe they recognize aspects of themselves or someone they know in the production. It also highlights the need for researchers to establish respectful terms of engagement for audiences who may offer a variety of interpretations to the artistic work. We point to possible ways that researchers and artists can address these ethical tensions to ensure that art-based health research is ethically rigorous as well as being creatively engaging.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.524

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.360
GPT teacher head0.540
Teacher spread0.181 · 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