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Record W3160370803 · doi:10.18432/ari29573

BOOK REVIEW

2021· article· en· W3160370803 on OpenAlexvenueno aff
U. Melissa Anyiwo

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPower (physics)Visual artsThe artsArtSet (abstract data type)Work (physics)AestheticsSociologyComputer scienceEngineeringPolitical scienceLaw

Abstract

fetched live from OpenAlex

Leading methodologist and arts-based researcher, Patricia Leavy, pioneered the method of social fiction, fiction-based research, or fiction as a research practice. Her latest release, Candy Floss Collection, is a set of three previously published novels, which together form installation art. This definitive and beautifully rendered work is important for several reasons. First, it demonstrates the power of fiction as a research method. Second, it is a beautiful piece of art. Third, it centres on powerful content, telling important and often invisible stories about women’s lives, aspirations, relationships, and daily struggles. Finally, this collection is a well-crafted piece of public scholarship that is imminently accessible to audiences inside and outside of academia. Overall, Candy Floss Collection is a triumphant piece of art, an exemplar of fiction as research, a highly accessible piece of public scholarship, and an engaging read. This is a significant and even game-changing work and ought to be recognized as such.

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)0.014
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: none
Teacher disagreement score0.268
Threshold uncertainty score0.897

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0030.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.2680.116

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 head0.329
GPT teacher head0.631
Teacher spread0.302 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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