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Record W4410840873 · doi:10.5817/ty2025-1-4

Doing the work: embodied cognition, ecological psychology, and screen actor training

2025· article· en· W4410840873 on OpenAlexfundno aff
Aaron Taylor, Douglas MacArthur, Javid Sadr

Bibliographic record

VenueTheatralia · 2025
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
FundersUniversity of Lethbridge
KeywordsEmbodied cognitionTraining (meteorology)PsychologyCognitionWork (physics)Ecological psychologyCognitive scienceEcologyCognitive psychologyComputer scienceEngineeringArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

Regarding acting and its training as a situated activity, best apprehended through an ecological, embodied focus on mutually constitutive interactions between the actor's mind, body, and performance environment, in this work we formally examine the development of undergraduate actors' performative skills – and requisite mental and physical resources – within an undergraduate pedagogical training program in screen acting. In meeting the actor's basic responsibility – the achievement of performative reality effects – successful actors must concretely demonstrate several core competencies based on situation-specific, task-oriented activities – demonstrable skills amenable to practical instruction and assessment within the classroom as well as to theoretical scrutiny from a pragmatic psychological perspective. Our interdisciplinary research program details the instruction and acquisition of a core set of aptitudes essential to the screen actor's successful engagement with the constraints and opportunities of a demanding, medium-specific production environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.746
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.088
GPT teacher head0.377
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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