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Record W3194833410 · doi:10.1111/jora.12665

Egyptian and Roma Adolescents’ Perspectives on Their Developmental Assets in Albania During the COVID‐19 Pandemic

2021· article· en· W3194833410 on OpenAlexaff
Diana Miconi, Eglantina Dervishi, Nora Wiium, Janique Johnson‐Lafleur, Silva Ibrahımı, Cécile Rousseau

Bibliographic record

VenueJournal of Research on Adolescence · 2021
Typearticle
Languageen
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsPandemicThematic analysisPsychologyPsychological interventionCoronavirus disease 2019 (COVID-19)Focus groupCoping (psychology)Descriptive researchMental healthDevelopmental psychologyAsset (computer security)Qualitative researchClinical psychologySociologyMedicinePsychiatrySocial scienceInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

This mixed‐method study explores the accessibility of developmental assets among Egyptian and Roma minority youth in Albania during the COVID‐19 pandemic. Six focus groups were conducted in August 2020 with Egyptian (n = 16) and Roma (n = 15) adolescents (14–20 years, Mage = 16.71; SDage = 2.00; 14 girls and 17 boys). In addition, adolescents rated how much they experienced each developmental asset. Descriptive and thematic analyses highlighted: (1) low developmental assets and barriers to accessing resources, (2) mental health concerns and coping strategies, (3) the role of proximal contexts of life, and (4) experiences within the society in terms of discrimination, integration, and contribution to society. Inter‐sectoral community‐based interventions are urgently needed to mitigate the impact of the pandemic on minority youth.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.222
GPT teacher head0.504
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2021
Admission routes1
Has abstractyes

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