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Record W3047418251 · doi:10.7202/1070271ar

Experiments with Book Festival People (Real and Imaginary)

2020· article· en· W3047418251 on OpenAlexvenueno aff
Beth Driscoll, Claire Squires

Bibliographic record

VenueMémoires du livre · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsAutoethnographySituatedSociologySloganScholarshipPersonhoodThe ImaginaryMedia studiesVisual artsVariety (cybernetics)Inclusion (mineral)The artsAestheticsArtSocial sciencePsychologyPsychoanalysisEpistemologyPolitical science

Abstract

fetched live from OpenAlex

While there are multiple approaches to researching cultural events, predominant academic frames tend to be either sociological or situated within a creative industries discourse. Neither of these approaches have supported sustained engagement with individual, interior experience at book festivals. Creative writers have imaginatively depicted these sites of author-reader interaction, and developing scholarship focuses on autoethnography and the phenomenological. In this article, we extend and materialise these approaches through a series of creative, arts-informed interventions: @AuthorsYurt, a personification on Twitter of the Edinburgh International Book Festival’s green room; Paper Dolls, a series of cut-out-and-dress dolls depicting audience members at a variety of book festivals across Europe, North America and Australia; and ClueButeDo, a satirical reworking of the audience feedback form at a small island crime festival in the UK. Each of the three experiments reveals aspects of personhood at book festivals, engaging with ideas of interiority, individuality, and experientiality, as well as of inclusion and exclusion. In pursuing this aim, we are guided by the autoethnographic slogan, “No Insight Without Inside, No Inside Without Outside” (Nunu Otot).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.227
Teacher spread0.209 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations5
Published2020
Admission routes1
Has abstractyes

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