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Record W2560629186 · doi:10.22230/src.2016v7n2/3a246

Innovation and Market Discipline in Scholarly Publishing

2016· article· en· W2560629186 on OpenAlexaffvenue
Rowland Lorimer

Bibliographic record

VenueScholarly and Research Communication · 2016
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPublishingMindsetOriginalityAudience measurementProfit (economics)BusinessMarket shareValue (mathematics)MarketingAdvertisingEconomicsPolitical scienceCreativityComputer science

Abstract

fetched live from OpenAlex

Background: In the face of extensive, developed-world library endorsement of open access (OA) and not-for-profit publishing, large commercial journal publishers are, paradoxically, increasing market share by means of economies of scale brought about in part by ownership concentration.Analysis: While the market success of commercial journal publishers may benefit from ownership concentration, it is argued that market-oriented innovation has also contributed to their market success. A review of the very lively state of market-oriented innovation in journal publishing and usage metrics is undertaken and three innovation proposals derived from commercial magazines are introduced.Conclusion and implications: The adoption of reader-focused features of commercial journals and the adaptation of the mobile-oriented strategy of commercial magazine publishers that respond to the modern digital information environment and mindset are recommended as strategically sound. Partnering with low-cost promoting, OA-oriented libraries may hobble the ability of not-for-profit journals to maximize their value to researchers.Originality/value: The weakness of OA as a constraining publishing strategy is brought forward and compared to readership building through innovation focused on usage.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0160.076
Open science0.0010.002
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 head0.074
GPT teacher head0.324
Teacher spread0.250 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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