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Record W7134826412 · doi:10.1093/pch/pxaf128

Caring for children and adolescents impacted by armed conflict: A rights-based approach

2025· article· en· W7134826412 on OpenAlexaffabout
Shazeen Suleman, Charles Hui, Ripudaman Minhas, Ashley Vandermorris

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsCanadian Paediatric Society
Fundersnot available
KeywordsArmed conflictMental healthHealth careConventionStatement (logic)Space (punctuation)Service providerHealth services

Abstract

fetched live from OpenAlex

Abstract Understanding how armed conflict impacts children and adolescents in wartime helps their care providers take the necessary time and space to attend to, and address, the unique exposures and health needs of newcomer families to Canada. This statement examines the direct, indirect, and remote effects of armed conflict on those disproportionately affected by violence, disruption, and displacement. Young people whose educational, socially supportive, and health service structures are seriously compromised or destroyed by armed conflict often experience huge gaps in access to care and live with long-unmet physical and mental health needs. Based on Canada's obligations under the United Nations Convention of the Rights of the Child, this statement offers strategies and resources that care providers can use to better recognize, appreciate, and address the effects of armed conflict—and migration experiences—as part of essential quality care.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0110.013
Scholarly communication0.0080.007
Open science0.0030.016
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.314
Teacher spread0.300 · 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 designNot applicable
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

Citations0
Published2025
Admission routes2
Has abstractyes

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