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Record W4388969002 · doi:10.3390/h12060138

Kinesthetic Experience: Emancipatory Corporeal Scores

2023· article· en· W4388969002 on OpenAlexaff
Celia Vara

Bibliographic record

VenueHumanities · 2023
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsMcGill University
Fundersnot available
KeywordsEmbodied cognitionAgency (philosophy)AestheticsArgument (complex analysis)Kinesthetic learningImitationNatural (archaeology)PaintingEmpathySociologyVisual artsPsychologyArtEpistemologySocial psychologyHistorySocial sciencePhilosophy

Abstract

fetched live from OpenAlex

This article investigates the corporeal practices by the Catalonian artist Fina Miralles (b.1950) in some of her performances during the 1970s. I specifically focus my analysis on the manner in which the artist verifies the existence of her body under the acute political restrictions on the body during the last years of Francoism (1939–1975). I argue that she does this by a process of sensorial investigations, which include painting, filming and touching natural elements, and moving them and leaving different types of tracks, which lead to generating corporeal scores and body mapping. I elaborate on the way that producing corporeal sensorial knowledge generated from her body mapping and kinaesthetic knowledge is a transgressive and emancipatory feminist intervention. My argument is that kinesthesia generates a process of body-mapping awareness within the body and its movement, which reinforces a sensorial way of knowledge that leads to a reconstitution of the body that function as corporeal agency. Based on feminist theories of embodiment and agency, taking the Carrie Noland concept of kinesthesia (2009) as a central analytical tool, and with a background as a psychologist, I approach this research with embodied methodologies (conversations with the artist, recreation of her actions, etc.) and draw mainly from research-creation methods and kinaesthetic empathy.

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)0.004
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0050.002
Open science0.0010.006
Research integrity0.0010.001
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 head0.138
GPT teacher head0.342
Teacher spread0.204 · 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
Published2023
Admission routes1
Has abstractyes

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