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Arts Therapies and the Intelligence of Feeling 11th European Arts Therapies Conference 21-24 September 2011, Lucca, Italy

2012· article· es· W1484398213 on OpenAlexaboutno aff

Bibliographic record

VenueComplutensian Scientific Journals (Complutense University of Madrid) · 2012
Typearticle
Languagees
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsFeelingPsychologyArtVisual artsSocial psychology

Abstract

fetched live from OpenAlex

Los dias 21, 22, 23 y 24 de septiembre tuvo lugar la XXIa Conferencia Europea sobre arteterapia, organizada por ECARTE, el Consorcio Europeo para la Educacion en Arteterapia. Desde el punto de vista de quien escribe, esta ha sido una de las conferencias mejor organizadas, mas interesantes y con mejor contenido a las que he tenido la ocasion de asistir. En el estuvieron presentes mas de quinientas personas procedentes de todos los lugares del mundo, desde Japon, Australia, Canada, EE.UU., Brasil, Chile, Israel, y todos los paises europeos. Uniendo la reflexion y la emocion, el pensamiento y el movimiento, la estructura del Congreso ha permitido combinar los espacios de la reflexion individual a traves de interesantes conferencias y comunicaciones, el dialogo y la comunicacion interpersonal, -a traves de debates sin la prisa de los tiempos-, la participacion de pequeno grupo -en los distintos talleres que sobre drama, danza-movimiento, musico y arteterapiay la participacion del gran grupo donde, en grandes talleres, tuvimos la oportunidad de compartir e intercambiar teorias, sensaciones, aplicaciones. El lugar ayudaba. La amurallada ciudad de Lucca, nos acogio en un septiembre todavia veraniego y nos invito a recorrer la ciudad buscando el lugar donde uno u otro taller tenia lugar. Las arquitecturas de mas cinco metros de alto bajo las que trabajabamos, llenas de frescos espectaculares, acompanaron nuestro trabajo lle-

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.007
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.102
GPT teacher head0.269
Teacher spread0.167 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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