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Record W2607340169 · doi:10.1017/s0008423916001086

Journal Publishing and Marketing in an Age of Digital Media, Open Access and Impact Factors

2017· article· en· W2607340169 on OpenAlexaffabout
Alex Marland

Bibliographic record

VenueCanadian Journal of Political Science · 2017
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPublishingPublicityImpact factorPolitical sciencePublic relationsPoliticsPosition (finance)BibliometricsLibrary scienceBusinessComputer scienceLaw

Abstract

fetched live from OpenAlex

Abstract Worldwide, the publishing industry has been compelled to change with digital media technology, and some traditional academic journals are struggling to adapt. This article examines the marketing and publicity actions available to the Canadian Journal of Political Science/Revue canadienne de science politique and similar flagship journals in an environment characterized by open access (OA) and impact factor (IF) metrics. It reviews the opportunities and threats presented by a movement towards publishing in ungated forums and pressure in the academic community to prioritize bibliometrics. It then looks at the experience, characteristics and comparative position of the Journal/Revue before reporting on perceptions and recommendations drawn from depth interviews with journal editors, presidents of the Canadian Political Science Association, and a university librarian, which are supplemented by suggestions from editorial board members. It concludes with proposals to address these circumstances head on, many of which are generalizable to other journals wrestling with marketing and publishing in the digital age.

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)0.047
metaresearch head score (Gemma)0.329
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Open science
Consensus categoriesMetaresearch, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0470.329
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0260.016
Science and technology studies0.0010.002
Scholarly communication0.1320.032
Open science0.0110.001
Research integrity0.0000.000
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 head0.663
GPT teacher head0.618
Teacher spread0.045 · 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

Citations12
Published2017
Admission routes2
Has abstractyes

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