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Record W3090807286 · doi:10.18432/ari29471

HEART OF THE MOUNTAIN

2020· article· en· W3090807286 on OpenAlexaffvenue
Barbara Bickel, R. M. Fisher

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTranceTransformative learningFormative assessmentThe artsAestheticsDialogical selfNarrativeCourseworkVisual artsPoetryCatharsisDialogicPsychologyBridge (graph theory)MetafictionDanceArtSociologyPsychoanalysisLiteraturePedagogyMedicineSocial psychologyAnthropology

Abstract

fetched live from OpenAlex

This arts-based co-inquiry engages the intersection of the Western medical-based world/reality and the Natural world/reality. To bridge these worlds the co-authors utilize a spiritual-based trance-formative practice using trance and arts-based inquiry. Instigated by a diagnosis and open-heart surgery of one of the co-authors, the purpose of their project is to offer an example of how a relational approach embracing Nature and art within a connective aesthetic of co-inquiry can offer deep healing and renewal. This spirit healing transcends the physical recovery from the medical intervention, extending a fearful experience into a gift of fearlessness. The writing weaves theoretical, dialogical script, images and poetic texts with an invitation to experience an eight minute art video that includes poetic voice, improvised vocal sounding, visual art and narrative reflection. The story explores the areas of intimate wit(h)nessing, therapeutic resilience and transformative learning at the physical, emotional and spiritual levels.

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.002
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0770.009

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 head0.114
GPT teacher head0.434
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 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
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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