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Record W2891643541 · doi:10.1386/jaah.9.2.237_1

Tapestries of resilience: An arts-based approach to enhancing the resilience of World Vision’s humanitarian staff

2018· article· en· W2891643541 on OpenAlex
Lama Majaj Ma, Crystal M. Penner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Arts and Health · 2018
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsWorld Wildlife Fund Canada
Fundersnot available
KeywordsSoftware deploymentThe artsResilience (materials science)Coping (psychology)Martial artsExperiential learningPsychologyPublic relationsReflexivityEmergency managementPsychological resilienceSociologyVisual artsPolitical scienceEngineeringPedagogySocial psychologyArtSocial sciencePsychotherapist

Abstract

fetched live from OpenAlex

Abstract Responding to the impact, community and individuals during a crisis is demanding for humanitarian workers. The need for resilience is crucial for the delivery of effective humanitarian aid and staff long-term emotional endurance. This article describes an arts-based approach aimed at enhancing the resilience of 53 World Vision (WV) staff in Asia at a weeklong Regional Disaster Management Team (RDMT) workshop. The purpose was to introduce responders to embodied artful experiences to develop coping skills and enhance their personal resilience to the impact of the response before, during and after deployment. The arts-based experiential sessions were embraced by the participants, with many acknowledging that they will engage in the arts as a reflexive practice during deployment.

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.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.058
GPT teacher head0.426
Teacher spread0.369 · 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