Risk behaviors and well-being among Egyptian and Roma adolescents in Albania during the COVID-19 pandemic: Vulnerability and resilience in a positive youth development perspective
Bibliographic record
Abstract
Introduction: Egyptian and Roma communities represent two of the most deprived and stigmatized ethnic minorities in Albania. However, research investigating vulnerability and well-being in youth from these communities is scant. Even less is known among Egyptian and Roma adolescents who dropped-out of school. Within a Positive Youth Development framework, we investigated among Egyptian and Roma adolescents: (1) risk behaviors, well-being, and developmental assets (personal and contextual); (2) associations of developmental assets with risk behaviors and well-being; (3) specificities by ethnicity, gender, and education. Methods: = 1.80; 47% girls; 53% school dropouts) completed a series of questionnaires in a community setting in August 2020 (first wave of the COVID-19 pandemic). Results: Binomial, Poisson and linear regression models indicated that Egyptian and Roma adolescents reported similar and high levels of risk behaviors, with boys reporting overall more risk behaviors than girls. Low level of well-being and of personal and contextual assets were reported. Girls reported higher family assets, positive values and social competencies than boys. The situation of adolescents attending school was overall not better than that of youth who had dropped out. Higher positive identity was associated with higher well-being. Discussion: Intervention and prevention efforts are urgently needed to support minority adolescents' development during and in the aftermath of the pandemic. They should address the structural factors which limit the availability of personal and contextual resources in minority youth's lives. Interventions aimed at building safer neighborhoods and providing safe access to schools for minority youth should be a priority and are essential to prevent the widening of inequalities during and after this health emergency.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".