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AGAINST EPISTEMOLOGICAL HIERARCHIES: ON THE VALUE OF FORMING BODILY KNOWLEDGE

2021· article· en· W3178259269 on OpenAlexaboutno aff
Ирина Сироткина

Bibliographic record

VenueEducation & Pedagogy Journal · 2021
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsnot available
Fundersnot available
KeywordsUnconscious mindCognitive sciencePsychologyCognitionKinesthetic learningValue (mathematics)FeelingEpistemologyTechneEmbodied cognitionCognitive psychologyComputer scienceSocial psychologyPhilosophy

Abstract

fetched live from OpenAlex

The article reveals such concepts as “metis,” “body techniques,” “practical skill,” “kinesthetic intelligence,” and “movement skill.” These concepts are united by the fact that the accumulation of knowledge is presented as a largely unconscious process in which muscles play the same role as the brain. The essence of these concepts can be expressed in the term “bodily knowledge,” which contrasts itself in the epistemological sense with codified practical knowledge, instructions, and rules – techne. Bodily knowledge is based on movements and muscle sensations. Russian physiologist I.M. Sechenov called this sensation “dark,” pointing out that such sensations are almost impossible to comprehend, describe, and analyze. However, such feelings cannot be entirely opposed to thought. This “smart skill,” as poet and writer Varlam Shalamov called it, can be considered a separate type of cognition. This article is an attempt to comprehensively discuss the concept of “body knowledge.”

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0050.000

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 head0.066
GPT teacher head0.401
Teacher spread0.335 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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