Rainbow Writes: Peer-Led Creative Writing Groups’ Potential for Promoting 2SLGBTQ+ Youth Wellbeing
Bibliographic record
Abstract
Though mainstream acceptance for the 2SLGBTQ+ community is on the rise, elevated risks of mental health challenges still pervade this community, particularly for youth growing up in this changing environment. Based on previous literature citing the benefits of creative interventions and youth autonomy, the current study sought to explore the implementation of an online, peer-led creative writing program as a possible means to increase emotional, psychological, and social wellbeing in 2SLGBTQ+ youth. Twenty self-identifying 2SLGBTQ+ youth from across Canada were recruited to form two 10-week, online peer-led creative writing groups titled “Rainbow Writes”. Based on Lerner et al.’s (2003) “Five Cs” of positive youth development, Rainbow Writes sought to alleviate some impacts of minority stressors in these 2SLGBTQ+ youth (14-18-years-old) within a COVID-19 context. Following a peer-led model, weekly writing exercises were led mainly by the youth. Mixed methods, in the form of a pre- and post- online survey, semi-structured interviews and a brief midway evaluation, were used to explore wellbeing outcomes and youth’s evaluation of the program. Thematic analysis, Reliable Change Index, and paired t-tests were used to analyze the data. Key qualitative findings demonstrated an increase in participants’ self-esteem and confidence as well as the importance of social connectedness and building 2SLGBTQ+ community, especially during the COVID-19 pandemic. Quantitative findings indicated positive changes in authenticity and other positive identity markers, and a slight decrease in anxiety symptoms. These findings contribute to the knowledge base on how to run successful creative writing interventions for 2SLGBTQ+ youth and demonstrate the potential of this program to help guide 2SLGBTQ+ youth through positive youth development.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".