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Record W2121738925 · doi:10.1353/arc.2011.0039

Music as Knowledge in Shamanism and Other Healing Traditions of Siberia

2003· article· en· W2121738925 on OpenAlexaboutno aff
Margaret Walker

Bibliographic record

VenueArctic Anthropology · 2003
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsnot available
Fundersnot available
KeywordsShamanismDanceNarrativeExperiential learningSingingPresentation (obstetrics)PsychologyAestheticsHistoryVisual artsSociologyPedagogyLiteratureMedicineArt

Abstract

fetched live from OpenAlex

Several presenters made the point that one cannot look at narrative alone, without taking into account the music, dance, and drumming that, in many settings, go along with it. One of these presenters was Marilyn Walker, who has had the good fortune to work with healers in Siberia. Although academic in approach, Marilyn’s paper also recognizes the importance of experiential ways of knowing. In her Quebec City presentation, she shared some of this experiential dimension by showing and commenting on videotaped segments featuring three Siberian healers. Walker’s paper discusses healing at several levels. In addition to several healing dimensions that she lists at the end of her paper, she mentions the physiological effects of music, dance, and drumming. Current research is leading to a better understanding of how trauma affects the brain and the body, and ways that various therapies, including new therapies focusing on sensorimotor effects, can promote healing. Along with these developments has come a greater appreciation and understanding among some mental health practitioners of some of the neuropsychological processes by which traditional practices such as narrative, singing, drumming, and dancing, may bring about healing.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.976

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.000

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 head0.077
GPT teacher head0.397
Teacher spread0.320 · 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 designTheoretical or conceptual
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

Citations17
Published2003
Admission routes1
Has abstractyes

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