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Record W3035308042 · doi:10.36510/learnland.v13i1.1007

Performative Writing as a Method of Inquiry With the Material World: The Art of the Imperative

2020· article· en· W3035308042 on OpenAlexvenueno aff
Esther Fitzpatrick, Alys Longley

Bibliographic record

VenueLEARNing Landscapes · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsnot available
Fundersnot available
KeywordsPerformative utteranceEmbodied cognitionPosthumanThe artsNarrativeSociologyAestheticsComputer scienceVisual artsArtEpistemologyLiteraturePhilosophy

Abstract

fetched live from OpenAlex

Understanding writing as a performative material practice, this paper highlights the “imperative” as a strategy to enhance writing practices in our classrooms and academic workshops. Drawing on posthuman theories and intra-active relationships, it describes how performative arts-based writing can provide a way to engage with the human and nonhuman, the embodied, sensory elements of our writerly worlds. Employing a critical collaborative autoethnographic methodology, the two authors provide a narrative account of a year as two research Fellows in a university exploring writing as a method of inquiry through designing and implementing a series of performative arts-based writing activities.

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)0.029
metaresearch head score (Gemma)0.035
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: Methods · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0080.064
Scholarly communication0.0190.012
Open science0.0020.009
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.031
GPT teacher head0.292
Teacher spread0.261 · 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
GenreMethods

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

Citations3
Published2020
Admission routes1
Has abstractyes

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