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Record W3088525755 · doi:10.1145/3409481.3409482

Interview with John Barber

2020· article· en· W3088525755 on OpenAlexaboutno aff
Claus Atzenbeck

Bibliographic record

VenueACM SIGWEB Newsletter · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipAction (physics)State (computer science)Digital humanitiesMedia studiesDigital scholarshipNew mediaDigital mediaSociologyLibrary scienceVisual artsArtArt historyWorld Wide WebComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

John F. Barber convenes with The Creative Media & Digital Culture Program at Washington State University Vancouver, USA. His scholarship, teaching, and creative endeavors arise from intersections of art, humanities, and technology and manifests as literary media art where he feels that practice-based research discovers and puts into action new knowledge. His radio and sound art are broadcast and exhibited internationally. His publications appear in Digital Humanities Quarterly, Digital Studies, ebr, Hyperrhiz: New Media Cultures, Leonardo, MATLIT (Materialities of Literature), Scholarly Research and Communication , and elsewhere. Barber curates The Brautigan Library , a collection of unpublished manuscripts, and was featured on This American Life.

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)0.021
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 score0.096
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0220.004
Scholarly communication0.0050.006
Open science0.0020.003
Research integrity0.0070.017
Insufficient payload (model declined to judge)0.0200.006

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 head0.049
GPT teacher head0.283
Teacher spread0.234 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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