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Record W4416311507 · doi:10.3389/fpsyg.2025.1689758

“There is no peace when you are excluded”: exploring peace and peacebuilding with children and youth affected by armed violence

2025· article· en· W4416311507 on OpenAlexafffund
Catherine Baillie Abidi

Bibliographic record

VenueFrontiers in Psychology · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPeace and Human Rights Education
Canadian institutionsMount Saint Vincent University
FundersMount Saint Vincent University
KeywordsPeacebuildingArmed conflictPrecarityVisionStructural violenceDemocracyHuman securityActive listeningCorporate governanceInterpersonal communication

Abstract

fetched live from OpenAlex

The global community is becoming increasingly fragile, plagued with intensifying armed violence, fracturing democratic governance processes, diminishing commitments and actions to protect basic human rights, and raging climate crises. Amid these complexities, children and youth are disproportionately impacted, and all signs point to increased precarity of their rights. Young people affected by armed violence are particularly suffering, thus understanding their rights and needs during and post conflict is essential to building effective peace and security. This research features the peace perspectives of 50 children and youth, all impacted by armed violence, and demonstrates the power of listening to young people's visions for peace. The key findings illustrate the importance of interpersonal peace, learning peacebuilding skills, and the essential role that children and youth play in building peace in their homes, schools, and communities. Recommendations for meaningful child engagement in the development of a Children, Peace, and Security Agenda are featured.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.156
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.024
GPT teacher head0.303
Teacher spread0.280 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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