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Record W4246479737 · doi:10.3138/jsp.37.1.1

Journals as Innovators and the Innovation of Journals: The Council of Editors of Learned Journals Keynote Addresses MLA Convention 2004

2005· article· en· W4246479737 on OpenAlexvenueno aff
Willis Goth Regier, James English, David C. Hanson

Bibliographic record

VenueJournal of Scholarly Publishing · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicPublishing and Scholarly Communication
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)ConventionSociologyMedia studiesLibrary scienceSocial scienceComputer science

Abstract

fetched live from OpenAlex

At the 2004 conference of the Modern Language Association in Philadelphia, the theme for the keynote session of the Council of Editors of Learned Journals (CELJ) was ‘Journals as Innovators and the Innovation of Journals’ — an idea suggested to us by Hayden Ward, retiring editor of Victorian Poetry (VP). VP itself has been as instrumental in prodding innovation in Victorian studies as in responding to change; likewise, all journals in the humanities aspire to help lead their respective fields, as well as to register how their fields are leading them. A related theme is how journal editors, precisely in thinking about ways to innovate, must periodically remake their journals; and how scholars who may be altogether new to editing, but who wish to speak to emerging fields, must invent new journals to spread the word. To address the latter theme, CELJ invited Willis Regier, who directs the University of Illinois Press, to offer recommendations about the new and ongoing lives and liveliness — and, occasionally, deaths — of university press journals. To address the former, CELJ asked James English, professor of English and comparative literature and chair of the English Department at the University of Pennsylvania, to discuss ways in which even the most forward-looking of journals in the humanities, Postmodern Culture, which he co-edited with Lisa Brawley for five years, could profit by re-examining its claims to being innovative. Both keynotes, edited for publication in JSP, provide a valuable distillation of their authors' scholarly and practical wisdom.

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)0.088
metaresearch head score (Gemma)0.137
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.930
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0880.137
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.006
Science and technology studies0.0200.014
Scholarly communication0.0700.032
Open science0.0090.016
Research integrity0.0420.030
Insufficient payload (model declined to judge)0.0290.009

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 head0.157
GPT teacher head0.314
Teacher spread0.157 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2005
Admission routes1
Has abstractyes

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