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Record W4379030567 · doi:10.1386/public_00149_1

Autoethnography and Somatic Modes of Attention

2023· article· en· W4379030567 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublic · 2023
Typearticle
Languageen
FieldPsychology
TopicDiversity and Impact of Dance
Canadian institutionsYork University
Fundersnot available
KeywordsAutoethnographyEmbodied cognitionDanceContext (archaeology)EthnographyAestheticsSociologyPsychologyGender studiesVisual artsAnthropologyEpistemologyArtHistory

Abstract

fetched live from OpenAlex

Somatic autoethnography integrates a materialist perspective that positions a dance ethnographer’s personal history--ethnicity, race, class or national origin—with modes of attention that highlight the impact of perception. From a contemporary neuro-science perspective somatic autoethnography can be articulated as an embodied form of research in which an act of mimesis in learning a dance form in a specific cultural context engages the neuro structures of the ethnographer to evolve new states of embodied cognition and an integration of perception, context/place, memory and imagination. In phenomenological terms, ethnographers transform their experience of their ‘lived-body’ through an intensive engagement in which the body of the performer through imitation becomes the object of the learner’s subjective identity. This project considers this topic from a historically contextual perspective of the author’s personal experience across three dance forms and cultural locations—Middle Eastern Raqs el Sharqi, dance among the Azande of South Sudan, and Japanese Nihon Buyo.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.222

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)0.0000.000

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 head0.066
GPT teacher head0.312
Teacher spread0.247 · 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