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Record W4377007231 · doi:10.24043/isj.422

The price of freedom: Open access, editorial labour, and prestige in academic publishing

2023· article· en· W4377007231 on OpenAlexvenueno aff
Adam Grydehøj, Ping Su

Bibliographic record

VenueIsland Studies Journal · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
FundersGuangdong Science and Technology Department
KeywordsPrestigePublicationPublishingOpen access journalSubject (documents)Political scienceLibrary sciencePublic relationsBusinessComputer scienceLawScopusMEDLINE

Abstract

fetched live from OpenAlex

This paper discusses tensions in journal editing and management, particularly for non-fee charging open access (diamond open access) journals. Even diamond open access journals and other journals published on a non-commercial basis are subject to financial and labour costs. Because diamond open access journals do not gain income from subscriptions or article processing charges (APCs), every published paper presents additional costs. Whereas commercially published journals depend upon substantial free academic labour, unfunded or underfunded diamond open access journals depend upon both substantial free academic labour and free non-academic labour. This encourages editors to be selective about the kinds of submissions on which they spend their time. The importance of maintaining a journal’s prestige, as measured through inclusion in bibliometric indices, incentivises further selectivity. Different kinds of papers are suitable for different kinds of journals. Even publications like Island Studies Journal that are radically accessible to authors and readers in diverse financial circumstances must make difficult choices when deciding what material to publish.

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.368
Teacher spread0.268 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2023
Admission routes1
Has abstractyes

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