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Record W4390105086 · doi:10.33524/cjar.v22i3.579

“Thing Power”: Art, Assemblage, and Entanglement as Practitioner Action Research

2022· article· en· W4390105086 on OpenAlexaffvenueabout
Timothy Shawn Beyak

Bibliographic record

VenueThe Canadian Journal of Action Research · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDeleuze and GuattariAffordanceAction researchAssemblage (archaeology)SociologyAction (physics)The artsPower (physics)PedagogyVisual artsAestheticsEpistemologyPsychologyArtHistoryPhilosophyArchaeology

Abstract

fetched live from OpenAlex

This paper explores an arts-based practitioner action research study that explores the artworks made by students from a Grade 11 History of Canada course in response to teaching and learning about the First World War. The practitioner considers the art-things (Bennett, 2015) of his students and the associated thing-power (Bennett, 2004) affordances. The work was informed by a rhizomatic methodology (Deleuze & Guattari, 1980/2000) that illuminated insights arising from interpretation and analysis of the educative assemblage and its concrete and abstract constituents and forces. The practitioner’s action research was informed by newness, unexpectedness, and difference (Deleuze & Guattari, 1968/1994) drawn from engagements with the students’ art-things and artist statements, which in turn enriched the personal and professional knowledge and educative practices of the author as well as his students’ learning because of knowledge drawn from this inquiry.

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)0.060
metaresearch head score (Gemma)0.041
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.005
Science and technology studies0.0200.122
Scholarly communication0.0240.025
Open science0.0040.021
Research integrity0.0060.007
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 head0.336
GPT teacher head0.451
Teacher spread0.116 · 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

Citations2
Published2022
Admission routes3
Has abstractyes

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