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Record W7120742750

O Ensino da Dança: uma via complementar para a formação contemporânea do ator

2022· article· pt· W7120742750 on OpenAlexaboutno aff
Skelling Desmeules (Universite d’Ottawa – Ottawa, Canadá), Marie-Eve

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2022
Typearticle
Languagept
FieldArts and Humanities
TopicArts and Performance Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDanceClass (philosophy)Work (physics)Qualitative researchField (mathematics)Vulnerability (computing)
DOInot available

Abstract

fetched live from OpenAlex

This interpretive qualitative research aims at understanding the corporal work in the class Dance for actors taught by Melanie Demers, invited artist during the 2014 winter semester at Ecole superieure de theatre in Universite du Quebec a Montreal. Using the concept of experience (Dewey, 2005) and the Activity theory (Engestrom, 1987; 1999), I studied how this class leads students to open themselves to their own bodies, to create a corporal writing, to develop internal and external conscienceness, to confront personal challenges related to the corporal work and to accept the vulnerability of their bodies in artistic expression.

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)0.010
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0160.034
Scholarly communication0.0110.008
Open science0.0020.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.050
GPT teacher head0.263
Teacher spread0.213 · 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 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
Published2022
Admission routes1
Has abstractyes

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