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Record W10367701 · doi:10.1007/s004150050352

The Scholarly Review Process at the University of Toronto Press

2004· dissertation· en· W10367701 on OpenAlexfundaboutno aff
Deborah Cooper

Bibliographic record

VenueJournal of Neurology · 2004
Typedissertation
Languageen
FieldArts and Humanities
TopicPublishing and Scholarly Communication
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsLibrary scienceMedia studiesProcess (computing)SociologyComputer science

Abstract

fetched live from OpenAlex

This report discusses the purpose of scholarly review and examines how the components of the process provide scholarly presses with a dependable system by which to select and develop manuscripts for publication. After examining scholarly review in a general sense, this report addresses the review process in detail as it occurs at the University of Toronto Press. The University of Toronto Press is the largest scholarly publisher in Canada and publishes in the social sciences and humanities disciplines. This report identifies safeguards that university presses integrate into the scholarly review process to ensure that the process consistently produces high-quality books. Two rounds of interviews were conducted to collect the data in this report. First, five University of Toronto Press editors were interviewed between July and August of 2002. The second set of interviews included four UTP authors as well as the Programme Manager of the Aid to Scholarly Publications Programme (funded by the Social Sciences and Humanities Research Council of Canada) and occurred in January of 2003. Information from these conversations was then integrated with what I learned during my internship at the press, as well as with research from the Canadian Federation for the Humanities and Social Sciences (CFHSS) Web site, the Journal of Scholarly Publishing, books about publishing with a scholarly press, the Manuscript Review Committee’s terms of reference, and a memorandum from a University of Toronto vice-president about the role of the university’s faculty publication board. This project report concludes by discussing issues that compromise the success of scholarly review and by proposing possible solutions to these problems.

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)0.004
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.713

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.011
Science and technology studies0.0050.003
Scholarly communication0.0140.004
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.5000.412

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 head0.030
GPT teacher head0.261
Teacher spread0.231 · 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 designQualitative
DomainEvaluation
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

Citations1
Published2004
Admission routes2
Has abstractyes

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