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Record W2775886205 · doi:10.29173/comp45

Touch, martial arts, and embodied knowledge

2017· article· en· W2775886205 on OpenAlexaffvenue
Scott Habkirk

Bibliographic record

VenueCOMPASS · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMartial Arts: Techniques, Psychology, and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMartial artsEmbodied cognitionEmpathyContext (archaeology)AestheticsVariety (cybernetics)PsychologyObject (grammar)Subject (documents)Visual artsSociologySocial psychologyArtComputer scienceHistoryArtificial intelligence

Abstract

fetched live from OpenAlex

Touch is essential to normal human development. It communicates a wide variety of things depending on the culture and the context. Through touch the boundary between subject and object becomes blurred and empathy can be cultivated. In the context of martial arts, touch can paradoxically lower levels of aggression,particularly in a traditional setting. This paper explores how touch is managed in martial arts and the embodied experiences that it can cultivate. Positivistic methodologies have revealed some of the benefits of martial arts on both physical and mental health, and studies that take a quantitative and culturally sensitive approach are revealing other dimensions of bodily experience.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.852
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.094
GPT teacher head0.433
Teacher spread0.338 · 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 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

Citations1
Published2017
Admission routes2
Has abstractyes

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