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Record W2607898736 · doi:10.29173/cjs28140

Future Challenges and Opportunities in Academic Publishing

2017· article· en· W2607898736 on OpenAlexaffvenue
Kyle Siler

Bibliographic record

VenueThe Canadian Journal of Sociology · 2017
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPublishingScholarly communicationDigitizationScientific communicationPublic relationsSociologyElectronic publishingOpen access publishingPolitical scienceLibrary scienceLawComputer scienceWorld Wide WebThe InternetTelecommunications

Abstract

fetched live from OpenAlex

Digitization and the rise of Open Access publishing is an important recent development in academic communication. The current publishing system exhibits challenges with cost, where many universities are forced to cancel journal subscriptions for economic reasons, as well as access, as scholars and the public alike often lack access to research published in paywalled subscription journals. Open Access publishing solves the access problem, but not necessarily cost problems. Universities and researchers are currently in a challenging, interstitial stage of scholarly publishing. Subscription journals still dominate scholarly communication, yet a growing imperative to fund and support Open Access alternatives also exists. Stakeholders, including faculty, university administrators, publishers, scientific funding institutions and librarians and governments alike currently strategize and fight for their professional and economic interests in the broader publishing system. Four main trends are suggested that will characterize the future of scholarly publishing: 1) antagonism with scholarly associations; 2) changes and innovations to peer review; 3) Scientific/Intellectual Movements around Open Access 4) publishing and new professional niches in the publishing landscape. This article suggests potential trajectories and outcomes for these various conflicts over the costs and benefits of academic publishing.

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)0.035
metaresearch head score (Gemma)0.030
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.744
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0140.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.000
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 head0.845
GPT teacher head0.567
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations35
Published2017
Admission routes2
Has abstractyes

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