MétaCan
Menu
Back to cohort
Record W4387193081 · doi:10.1177/21582440231200360

Socially Situated Experiences of Substance Use: A Photo Elicitation Pilot Study

2023· article· en· W4387193081 on OpenAlexafffund
Niki Kiepek, Christine Ausman, Andrea Murphy, Tommy Brothers

Bibliographic record

VenueSAGE Open · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsPhoto elicitationPsychologySocial psychologySubstance useCoping (psychology)SituatedApplied psychologyPsychotherapistSociologyClinical psychology

Abstract

fetched live from OpenAlex

Our study was designed to pilot a photo elicitation methodology and undertake preliminary examination of substance use from the perspectives of two potentially disparate groups. Photo elicitation methodology involved participant generated photos and elicitation interviews to purposefully explore (i) how people who use substances depict and discuss their own substance use, and (ii) how professionals who prescribe/dispense pharmaceuticals depict and portray how substances impact the lives’ of patients/clients. Individuals who use substances told “stories of self.” Health providers blended “stories of others” and “stories of social worlds” that indirectly revealed “stories of self.” All participants confronted dominant social perspectives, offering alternative interpretations and challenging such opinions as incomplete or erroneous. The social nature of substances held contrasting perspectives, with health professionals seeing incentives of “fitting in” with “peers using” and a “coping strategy” to reduce social anxiety. Participants who use substances told stories of positive social connections through shared experiences of substance use and increased effects of sociability. Findings may contribute to nuanced understandings to destigmatise and mitigate Othering.

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

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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
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 score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.788
GPT teacher head0.665
Teacher spread0.122 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueSAGE OpenSame topicParticipatory Visual Research MethodsFrench-language works237,207