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Record W2114338385 · doi:10.1177/000841740206900405

Occupational Therapy Intervention with Children Survivors of War

2002· article· en· W2114338385 on OpenAlexvenueno aff
Salvador Simó-Algado, Nina Mehta, Franciscus Kronenberg, Lynn Cockburn, Bonnie Kirsh

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2002
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyIntervention (counseling)SpiritualityPsychologyClinical psychologyMedicinePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

A preventive occupational therapy program with children surviving the Kosovo conflict is examined. The objective of the program was to facilitate the emotional expression of traumatic experiences in order to prevent the development of future psychological problems. The intervention was based on a community-centred approach with spirituality as a central focus of the intervention. The Model of Human Occupational and the Occupational Performance Process Model were utilized to guide the identification and intervention of occupational performance issues. The children's return from a land of war to a land of children demonstrates the potential of occupational therapy intervention in this field. With increasing awareness of populations facing social and political challenges, there is a growing importance of the concept of occupational justice and the need to work against occupational apartheid.

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)0.002
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.107
GPT teacher head0.408
Teacher spread0.301 · 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

Citations42
Published2002
Admission routes1
Has abstractyes

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