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Record W1868352903 · doi:10.18438/b8hc87

Traditional Factors of Fit, Perceived Quality, and Speed of Publication Still Outweigh Open Access in Authors’ Journal Selection Criteria

2012· article· en· W1868352903 on OpenAlexvenueno aff
Michelle Dalton

Bibliographic record

VenueEvidence Based Library and Information Practice · 2012
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsDirectoryPublishingQuality (philosophy)Open access publishingComputer scienceSubject (documents)Library sciencePsychologyPolitical science

Abstract

fetched live from OpenAlex

Objective – To determine the extent to which the open access (OA) status of a journal influences authors in their journal selection decisions and to analyze the sources of funding for the article-processing charges (APCs) applied in professional OA publishing.
 
 Design – Survey questionnaire.
 
 Setting – The international open access scholarly publishing sector.
 
 Subjects – 1,038 researchers across all academic disciplines who have recently published work in open access journals that charge APCs. 
 
 Methods – Journals listed in the Directory of Open Access Journals were stratified into seven discipline clusters, and systematic random sampling was used where possible to collect a sample of up to 15 journals per cluster that levy APCs. For each individual journal, the authors of the 15 most recently published articles (working from 2010 backwards) were invited to complete a web-based questionnaire on the factors influencing their choice of journal and the source(s) used to fund processing charges. Additional background information about the authors and journals was also collected and merged with the survey responses. 
 
 Main Results – The results of the survey identified the fit of the article with the journal’s subject area, the perceived quality or impact of the journal, and the speed of the peer-review and publishing process as the dominant factors in the journal selection decision of authors. All three aspects were judged as either “very important” or “important” by 80% or more of respondents – significantly higher than the corresponding figure of 60% in relation to the open access status of the journal. 
 
 The analysis also indicated that two key elements appear to influence how APCs are funded: the research discipline and the country of origin of the author. The use of research grants to fund charges is more prevalent in scientific disciplines than in the humanities, whilst researchers based in lower-income countries more frequently identify APCs as a barrier than those in higher-income countries. Grants and institutional funding tend to be the primary sources of funding for journals with higher APCs, whilst personal funding is utilised more often in cases where the fee is less than $500.
 
 Conclusion – Despite the increasing focus on the accessibility and visibility of research, academics still appear to place a greater value on ‘who’ rather than ‘how many’ readers access their research, and consequently traditional factors still persist as the main determinants in an author’s choice of journal. The future success of the APC model, compared with the traditional subscription-based or hybrid models, will ultimately depend on the ability of authors to obtain the necessary funding to pay such charges, combined with the extent to which the quality of services offered by open access publishers is perceived as being commensurate with the associated publishing fees.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearchScholarly communication
Domain: Incentives · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.019
metaresearch head score (Gemma)0.075
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesBibliometrics, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.075
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0130.024
Science and technology studies0.0000.000
Scholarly communication0.0060.436
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.741
GPT teacher head0.606
Teacher spread0.134 · 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

Labeled directly by 2 models reading the full record.

MetaresearchScholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational
DomainIncentives
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

Citations2
Published2012
Admission routes1
Has abstractyes

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