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Record W4381513018 · doi:10.1177/10778004231176089

Beautiful Mis/takes

2023· article· en· W4381513018 on OpenAlexaff
Jee Yeon Ryu

Bibliographic record

VenueQualitative Inquiry · 2023
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsYorkville University
Fundersnot available
KeywordsImprovisationPraxisPianoReflexivityHumanismPoetryVisual artsThe artsAestheticsArtPiano pedagogySociologyMusic educationPsychologyPedagogyLiteratureEpistemologyPhilosophyArt history

Abstract

fetched live from OpenAlex

In the following three fragments, I illustrate how I am learning to practice reflexivity through the arts—with a story, piano improvisation, and poem—to evoke possibilities for more empathetic and humanistic ways of teaching and learning that embody what truly matters at the heart of children’s lived and living experiences of exploring music and piano playing. I integrate text, digitally edited photographs, and music video as artistic expressions of my praxis toward more heartful, healing, and joyful ways of teaching and learning.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0060.006
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0300.010

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 head0.435
GPT teacher head0.592
Teacher spread0.157 · 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 designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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