Let’s do this together: an integration of photovoice and mobile interviewing in empowering and listening to LGBTQ+ youths in context
Bibliographic record
Abstract
Evidence from a meta-analysis suggested that lesbian, gay, bisexual, transgender, and queer (LGBTQ+) youth experience elevated levels of victimization in schools as compared to their heterosexual peers, and that victimization was shown to be persistent and lasting, indicating that school environments are hostile. These findings point to the need to better understand youths’ own efforts in becoming more aware and engaged in impacting systemic inequities. Photovoice and mobile interviewing, two relatively novel qualitative methodologies in the field of LGBTQ research, are methodologies that involve the participants by 1) taking photos of interest as a means of critical discussion, and 2) moving alongside the researcher in a participant-chosen area and have critical discussions highlighted by the visual cues. The goal of this paper is to highlight ways of listening to opinions of LGBTQ youth that are contextualized in the environments in which they are victimized.
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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 | 0.035 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".