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Record W2159507530 · doi:10.1177/000271620157500107

The Political Economy of War-Affected Children

2001· article· en· W2159507530 on OpenAlexaff
Steven Hick

Bibliographic record

VenueThe Annals of the American Academy of Political and Social Science · 2001
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoliticsRefugeePolitical scienceContext (archaeology)GlobalizationArmed conflictCriminologyRelation (database)Cold warPolitical economySpanish Civil WarDevelopment economicsSociologyLawHistoryEconomics

Abstract

fetched live from OpenAlex

The nature of armed conflict has changed since the rise of globalization and the end of the Cold War. Now wars predominantly take the lives of civilians, over half of whom are children. This article examines the effects of armed conflict on children. In particular, it discusses refugee and internally displaced children, child soldiers, the sexual assault and exploitation of girls, and children traumatized by war. How the international community should respond to protect children and prevent war is explored in relation to the political and economic context within which wars occur.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0040.001
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.126
GPT teacher head0.494
Teacher spread0.368 · 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 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

Citations22
Published2001
Admission routes1
Has abstractyes

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