Do Mock-Ups, Presentations of Evidence, and Q&As Help Participants Voice their Opinions During Focus Groups and Interviews About Supervised Injection Services?
Bibliographic record
Abstract
Controversial facilities (e.g., supervised injection services (SIS), methadone clinics, and social housing) may require feasibility studies that asses their acceptability among community stakeholders before their implementation. However, controversies about these facilities may make stakeholders ambivalent or hesitant to express opinions about them because various sources of information disagree about their harms and benefits. We responded to this challenge by creating and piloting the use of “grounding aids” or tools, objects, and methods used before qualitative data collection to provide research participants with an experience in which they can learn about how the controversial facility operates in practice. Before interviews and focus groups in a recent SIS feasibility study we conducted, participants were introduced to three of these grounding aids: a physical mock-up of an SIS, a presentation regarding evidence on SIS, and a Q&A with SIS staff. We then asked additional questions in the interviews and focus groups about participants’ experience with these grounding aids. With few exceptions, participants generally perceived the grounding aids to help them express their opinions without feeling that we were directing their opinions about SIS. Participants’ reasons for this included that the grounding aids helped them experience unfamiliar aspects of SIS visually and concretely, served as a cue for questions and as a reference for discussions, and personalized SIS and its operations. We also observed that they voiced less hesitancy overall regarding SIS than participants in our previous feasibility studies where we did not employ these grounding aids before data collection. Researchers planning to study perceptions of controversial facilities or other phenomena about which sources of information tend to disagree on may want to consider creating, evaluating, and using grounding aids to improve participant responsiveness.
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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 | 0.160 | 0.278 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.017 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".