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Record W2612501243 · doi:10.1177/0743558416684950

Complexity of Risk: Mixed-Methods Approach to Understanding Youth Risk and Insecurity in Postconflict Settings

2017· article· en· W2612501243 on OpenAlexfundno aff
Laura K. Taylor, Christine E. Merrilees, Dinka Čorkalo Biruški, Dean Ajduković, E. Mark Cummings

Bibliographic record

VenueJournal of Adolescent Research · 2017
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
FundersNanovic Institute for European StudiesQueen's UniversitySveučilište u ZagrebuQueen's University BelfastUniversity of Notre DameKroc Institute for International Peace Studies, University of Notre DameAmerican Psychological Foundation
KeywordsEthnic groupPsychologyContext (archaeology)Focus groupSocial psychologyDevelopmental psychologyPolitical scienceSociologyGeography

Abstract

fetched live from OpenAlex

In settings of intergroup conflict, identifying contextually relevant risk factors for youth development is an important task. In Vukovar, Croatia, a city devastated during the war in former Yugoslavia, ethno-political tensions remain. The current study utilized a mixed-methods approach to identify two salient community-level risk factors (ethnic tension and general antisocial behavior) and related emotional insecurity responses (ethnic and nonethnic insecurity) among youth in Vukovar. In Study 1, focus group discussions ( N = 66) with mothers, fathers, and adolescents of age 11 to 15 years old were analyzed using the constant comparative method, revealing two types of risk and insecurity responses. In Study 2, youth ( N = 227, 58% male, M = 15.88, SD = 1.12 years) responded to quantitative scales developed from the focus groups, discriminate validity was demonstrated, and path analyses established predictive validity between each type of risk and insecurity. First, community ethnic tension (i.e., threats related to war/ethnic identity) significantly predicted ethnic insecurity for all youth (β = .41, p < .001). Second, experience with community antisocial behavior (i.e., general crime found in any context) predicted nonethnic community insecurity for girls (β = .32, p < .05) but not for boys. These findings are the first to show multiple forms of emotional insecurity at the community level; implications for future research 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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.311
GPT teacher head0.498
Teacher spread0.187 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2017
Admission routes1
Has abstractyes

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