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Record W4384199271 · doi:10.5565/rev/ciencies.466

L'Art a STEAM. Estratègies per a fomentar l'art en els projectes STEAM.

2023· article· ca· W4384199271 on OpenAlex
Carmen Arrufat, Sebastian Martin

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

VenueCiències revista del professorat de ciències de Primària i Secundària · 2023
Typearticle
Languageca
FieldPsychology
TopicHealth, Education, and Physical Culture
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsHumanitiesArtStudioContemporary artArt historyVisual artsPerformance art

Abstract

fetched live from OpenAlex

Aconseguir dur a terme projectes en què totes les disciplines STEAM s'enriqueixin mútuament implica conèixer els objectius fonamentals i processos propis de cadascuna d'elles. Bea Rey i Carmen Arrufat, com a docents especialitzades en art, en diàleg amb Sebastian Martin de Tinkering Studio, presenten una experiència concreta d'”Exploring Balance” realitzada a l'aula d'art de l’escola La Vall amb la finalitat d'oferir algunes claus fonamentals que facilitin la integració de l'art de manera equilibrada i coherent en projectes STEAM, incidint en el valor i els beneficis que l'art pot aportar a aquest tipus de projectes.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.018

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 head0.030
GPT teacher head0.356
Teacher spread0.326 · 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