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Record W2553484414 · doi:10.1386/tear.14.3.275_1

Senses to cultivate the collective consciousness: Physical theatre, an experimental approach to product design education

2016· article· en· W2553484414 on OpenAlexaff
Tommaso Maggio

Bibliographic record

VenueTechnoetic Arts · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsAssumption University
Fundersnot available
KeywordsConsciousnessIntellectPerceptionProduct (mathematics)AestheticsCollective unconsciousObject (grammar)Context (archaeology)Field (mathematics)The artsAction (physics)Social consciousnessSociologyPsychologyEpistemologyVisual artsArtLinguisticsPhilosophyHistoryPsychoanalysisMathematics

Abstract

fetched live from OpenAlex

Abstract Consciousness and perception of reality are related to internal and external factors as the sum of collective and social interactions. Attila Grandpierre in his ‘The physics of collective consciousness’ underlined the prime role of performing arts quoting the words of Vekerdy, who said that theatrical artists especially in the ancient Japanese Noh Theatre have a great effect on audience in three ways: using words, hearing by movements, through seeing and the use of intense emotion. Generally in the design field the relation between user and the product is stressed; on the other hand, in the theatre field the ability to explore and underlining the social impact of a specific object or action is important. We might assume that each of us perceives the world differently according to the culture that we are a part of. The ancient Aristotle’s peripatetic School and the context of Zen Buddhism highlighted the senses and experimental knowledge as the first important tools to cultivate intellect. This article will describe an experimental blend created in Thailand between physical theatre and design education.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.013
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.051
GPT teacher head0.287
Teacher spread0.236 · 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 designQualitative
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

Citations1
Published2016
Admission routes1
Has abstractyes

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