A Qualitative Exploration of Information and Communication Technology Use among Lesbian, Gay, Bisexual, Transgender, Queer Emerging Adult Migrants Before and After Arrival in the United States
Bibliographic record
Abstract
Information and communication technologies (ICTs) have been shown to facilitate LGBTQ+ emerging adult development as well as international migration. Nonetheless, few studies have examined pre- and post-migration ICT use among LGBTQ+ emerging adult migrants. To fill this knowledge gap, we conducted online interviews with 37 LGBTQ+ individuals (ages 20–25) who migrated from various countries to different U.S. states. Constructivist grounded theory was used to identify four themes: In and out: Balancing identity exploration with identity concealment when using ICTs in the country of origin; relying on ICTs to prepare for migration to the United States; using ICTs to find housing, work, and friends in the United States; and drawbacks of using ICTs in the United States. ICTs facilitated identity development and eased integration but exposed participants to harassment and scams. Findings indicate that closely investigating ICT use can enhance developmental and migration theories, improve research, and inform programs and services.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".