Resilience Portfolio: Strengths Promoting Well-Being in Sexually Diverse Youth
Bibliographic record
Abstract
Sexually diverse youth (SDY), including lesbian, gay, bisexual, queer, and pansexual youth, face significant challenges, being nearly three times more likely to experience victimization compared to their heterosexual peers. Among SDY, bisexual youth are at higher risk of interpersonal violence than gay youth. It is well documented that interpersonal violence can lead to serious consequences for SDY, such as depression and trauma symptoms. However, the outcomes associated with victimization are heterogeneous, and some youth appear to fare better despite adversity. This study aimed to explore the strengths that help SDY navigate their challenges and contribute to their well-being. An online survey was conducted, and 4,122 youth aged 14 to 25, including 251 gay youth and 585 bisexual youth, completed measures of victimization and indicators derived from the Resilience Portfolio Model: Scales for Youth. This study compared victimization rates, level of trauma symptoms, and level of well-being of gay youth, bisexual youth, and heterosexual youth using ANOVAs. Multiple linear regressions were then conducted to identify the strengths associated with well-being among youth according to their sexual orientation. SDY had a higher level of trauma symptoms and a lower level of well-being than heterosexual youth. SDY also had fewer strengths that promote resilience than heterosexual youth. Notably, purpose stood out as the most significant predictor of well-being among all sexual orientations. Practitioners working with SDY could assist them in developing strengths-especially a sense of purpose-to build their resilience and enhance their well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".