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Record W2990595930 · doi:10.7146/peri.v16is7.115118

Forholdet mellem det verbale sprog og kropssproget i udvalgte grønlandske teaterproduktioner i 2017*

2019· article· da· W2990595930 on OpenAlexaboutno aff
Arnaq Brandt Johansen

Bibliographic record

VenuePeripeti · 2019
Typearticle
Languageda
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSymbol (formal)GestureContext (archaeology)HumanitiesArtArt historyPhilosophyLinguisticsHistoryArchaeology

Abstract

fetched live from OpenAlex

Med udgangspunkt i Nicole Tersis et aliis Words and Gesture. An Inuit storyteller in East Greenland (2016) og Marcel Mauss’ Techniques of the Body (opr.1936/1973), vil min artikel fokusere på kroppen som kulturelt symbol i forbindelse med udvalgte grønlandske teaterproduktioner, som jeg har observeret i løbet af 2017. Formålet er i denne kontekst at fremanalysere forholdet mellem det verbale og det kropslige sprog og at vurdere, hvordan der er tale om et ’særligt grønlandsk’ udtryk i performansen.As a starting point with Nicole Tersis et aliis Words and Gesture. An Inuit storyteller in East Greenland (2016) and Marcel Mauss’ Techniques of the Body (1936/1971), my article will focus on the body as a cultural symbol in Greenlandic theatre productions which I have observed in 2017. The purpose of the context is to analyze the relationship between the verbal and body language and to evaluate how there is a ’particularly’ Greenlandic expression in the performances.

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)0.001
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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
Published2019
Admission routes1
Has abstractyes

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