Socially Situated Experiences of Substance Use: A Photo Elicitation Pilot Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".