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Record W4385569299 · doi:10.1386/jaac_00041_2

Spaces of reconnection

2023· article· en· W4385569299 on OpenAlexaff
Taiwo Afolabi, Emma Shercliff, Elaine Speight

Bibliographic record

VenueJournal of Arts & Communities · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsCreativityTheme (computing)Coronavirus disease 2019 (COVID-19)AestheticsMedia studiesPandemicSet (abstract data type)Visual artsSociologyHistoryArtPsychologySocial psychologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

In this editorial we pick up again the theme of ‘connection’. Over the last year, the disconnections from our creative communities provoked by the COVID-19 pandemic have loomed large on our horizon: how do we set about reconnecting? Articles presented in this volume examine these disconnections and explore the ways artists, designers, curators, photographers, gamers, dancers and others draw upon expanded approaches to creativity, initiating imaginative and resourceful ways to reconnect with their audiences and communities.

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)0.005
metaresearch head score (Gemma)0.016
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 score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0110.030
Scholarly communication0.0220.026
Open science0.0030.017
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0220.004

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 head0.144
GPT teacher head0.312
Teacher spread0.168 · 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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