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Record W2268906875 · doi:10.3138/jsp.47.2.180

What We Still Don't Know About Peer Review

2016· article· en· W2268906875 on OpenAlex
Omar Sabaj, Carlos González Vergara, Álvaro Piña-Stranger

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Scholarly Publishing · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsnot available
Fundersnot available
KeywordsEmpirical researchComprehensionMechanism (biology)Process (computing)Field (mathematics)Production (economics)Object (grammar)SociologyEpistemologyPeer reviewSocial sciencePolitical scienceComputer scienceLawEconomics

Abstract

fetched live from OpenAlex

Despite criticisms, the peer review process (PRP) is undoubtedly well established as an official and legitimated mechanism for evaluating and controlling scientific production. Although PRP has been a prominent object of study, we argue in this article that empirical research on PRP has not been addressed in a comprehensive way. Nine categories were applied to 150 empirical research articles on the topic with results revealing various gaps in empirical PRP research: (1) the research has been dedicated to the evaluation of the system rather than to the actual description of PRP as a concrete socio-discursive practice; (2) the most productive group of studies considers the multiple relationships between the sociological attributes (socio-demographic or scientometrical) of the actors (authors, reviewers, and editors) and the results of the process but does not take into account the texts exchanged by those actors; and (3) the few studies that do analyze the texts interchanged in the process do not take into account any of the variables included (such as scientometrical data, agreement, and rejection rates) in the more productive areas of the field. This lack of integration among the methodological approaches to PRP results in a partial comprehension of this important process, which determines the production and dissemination of an important part of scientific knowledge.

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.

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)0.473
metaresearch head score (Gemma)0.571
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Scholarly communication, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4730.571
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.1520.197
Open science0.0070.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.002

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 head0.597
GPT teacher head0.489
Teacher spread0.107 · 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