Digital microaggressions and LGBTQ+ youth: exploring potential impacts and opportunities for educational intervention
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
LGBTQ+ youth frequently leverage the affordances of internet-enabled information and communication technologies (ICTs) to support their identity development, mental health, and well-being. Yet, anti-LGBTQ+ intolerance simultaneously persists in their digitally mediated contexts—including in the form of digital microaggressions. Data from an online survey of LGBTQ+ youth (age 14–24) residing across the United States, United Kingdom, and Canada were used to explore the relationships between six types of digital microaggressions, perceived stress, mental health, and psychological well-being through structural equation modelling. Findings suggest that exposure to some types of digital microaggressions may produce direct, incremental, and negative impacts on LGBTQ+ youth. Experiencing and witnessing discriminatory digital microaggressions had the most consistently significant relationships. Opportunities for future scholarship and insights for supportive intervention by caregivers, educators, and other professionals are discussed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it