Dialogical Consent Practices in Research With 2S‐LGBTQ+ Youth
Bibliographic record
Abstract
ABSTRACT The limits of research consent processes come into quick relief when researching with marginalized youth, limits we have tested and contested in a research partnership with LU and GC in Canada. LU is a horizontal research collective, while GC is a 2S‐LGBTQ+ non‐profit. Together we initiated a project in 2022 to study Equity, Diversity and Inclusion (EDI) practices with community organizations, developing a series of youth workshops. We grounded our ethics protocol in GC's everyday consent practices in work with youth, including candid conversations about power, intersectionality, respect, identity, and language. We co‐developed a video consent process to facilitate youth self‐consent in the workshops. While parents, guardians, or caregivers often must consent on behalf of youth, this may pose risks for 2S‐LGBTQ+ youth in non‐affirming homes and may further deepen their alienation or exclude them from participation. Importantly, GC does not require parental, guardian, or caregiver consent for accessing their services but provides for youth self‐consent. Youth self‐consent, moreover, is supported by human rights, educational, and social work practices. GC's consent practices were integrated into our research including our ethics protocol. Our findings identify both challenges in having self‐consent accepted by the REB, the precarity of nonprofits and long‐term community‐engaged research with short‐term funding; and successes in strong community relationships, interviews, and innovative methodologies. We propose a methodological framework for dialogical youth self‐consent that can support intersectional 2S‐LGBTQ+ youth access to participation in research, in turn supporting paths to agency through expressing their ideas and perspectives. Moreover, we foreground consent as being continuously negotiated and reaffirmed in dialogue with 2S‐LGBTQ+ youth themselves, highlighting the transformative potential of participatory self‐consent processes for youth.
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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 | 0.226 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.040 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".