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Record W4392884980 · doi:10.1111/pops.12962

Urban Colombian youths' perspectives on the armed conflict and possibilities for ways forward

2024· article· en· W4392884980 on OpenAlexafffund
Laura Pareja Conto, Gabriel Vélez, Angelica Restrepo, Holly Recchia, Roberto Posada, Cecilia Wainryb

Bibliographic record

VenuePolitical Psychology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicConflict, Peace, and Violence in Colombia
Canadian institutionsConcordia University
FundersSocial Sciences and Humanities Research Council of CanadaConcordia University
KeywordsArmed conflictPsychologyCriminologySocial psychologySociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract In the aftermath of intractable armed conflict, adolescents can play a critical role in the process of reconciliation and the construction of a culture of peace. The meanings they construct about these processes are a core aspect of their engagement (or lack thereof) in peace‐building initiatives. This study sought to document adolescents' perspectives on the Colombian armed conflict and the 2016 peace treaty, as well as their preferred resolutions to move forward after decades of harm and division. We interviewed 77 adolescents (39 girls, 38 boys) ranging from ages 14 to 19 years ( M = 16.49, SD = .95) from two public schools in Bogotá, Colombia. We asked youth open‐ended questions about the history of the armed conflict, their position toward the peace accord, and their proposed optimal resolutions to address harms committed by the Fuerzas Armadas Revolucionarias de Colombia—Ejército del Pueblo (FARC). Using thematic analysis, we identified three overall themes in adolescents' responses: (1) cynicism toward peace and desires for retribution, (2) improving the lives of those they thought were most impacted, and (3) restoring relationships and ending cycles of violence. We discuss the implications of our findings for psychological scholarship, peace education, and politics of reconciliation in light of Colombia's current political and social climate.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.419
Teacher spread0.320 · 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 designTheoretical or conceptual
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

Citations2
Published2024
Admission routes2
Has abstractyes

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