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Record W2049832016 · doi:10.1080/13533310308559339

A CIMIC Contribution to Assessing Progress in Peace Support Operations

2003· article· en· W2049832016 on OpenAlexaff
Larry Jenkins

Bibliographic record

VenueInternational Peacekeeping · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsNormalityPolitical sciencePopulationData collectionPeacekeepingPublic administrationEconomic growthPublic relationsDevelopment economicsSociologyEconomicsPsychologySocial scienceSocial psychology

Abstract

fetched live from OpenAlex

CIMIC (civil-military cooperation) has become recognized as a central activity in peace support operations. CIMIC personnel interact not only with the local population but also with international groups providing humanitarian aid and hoping to bring social and economic stability to the area. The article summarizes some of the data collection and reporting on the return to normality that took place in Bosnia and Herzegovina and Kosovo. It advocates a stronger recognition by CIMIC groups of the need and responsibility to observe and report systematically on social and economic progress in their area of operation.

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)0.007
metaresearch head score (Gemma)0.017
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: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0140.011
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.027
GPT teacher head0.385
Teacher spread0.358 · 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

Citations8
Published2003
Admission routes1
Has abstractyes

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