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Record W4221082608 · doi:10.5209/aris.75542

Case Study First Aid in Art Therapy and its liberating role in Bosnia and Herzegovina Temporary Reception Centers for Migrants and Refugees

2022· article· en· W4221082608 on OpenAlexfundno aff
Teresa Lousa, Malena Hughet

Bibliographic record

VenueArte individuo y sociedad · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaFederation for the Humanities and Social Sciences
KeywordsBosnianRefugeeArchetypeContext (archaeology)Humanitarian aidArt therapyRelief WorkPsychologySociologyPsychotherapistHistoryMedicinePolitical scienceArtLawArchaeologyLiteraturePhilosophyMedical emergency

Abstract

fetched live from OpenAlex

First Aid in Art Therapy is a therapeutic approach carried out in Bosnian migrants and refugee camps from October 2019 to the present.. In an extremely challenging context for therapists and beneficiaries, Art Therapy sessions were held according to the methodology of free creative expression, with a high degree of adjustability. A non-directed work prioritizing each participant’s needs, spontaneity, and the factor of transitoriness, either of conditions or of emotions, was revealed to be the appropriate approach within a context of humanitarian crisis. In this study, the theoretical foundations of Carl Jung and Nise da Silveira[1] were used, especially with regard to the concept of Archetype, which is essential for a better understanding of the images produced in these sessions. It could be observed in the migrants and refugees’ work that certain repeated patterns appeared, for example: feminine figures and mandalas: which coincide with two strong archetypes that will be highlighted.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.028

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 studies0.0150.004
Scholarly communication0.0030.001
Open science0.0020.004
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.055
GPT teacher head0.282
Teacher spread0.227 · 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 designCase report
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

Citations2
Published2022
Admission routes1
Has abstractyes

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