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Record W2302088999 · doi:10.18438/b84w67

Open Access Papers Have a Greater Citation Advantage in the Author-Pays Model Compared to Toll Access Papers in Springer and Elsevier Open Access Journals

2016· article· en· W2302088999 on OpenAlexvenueno aff
Elaine Sullo

Bibliographic record

VenueEvidence Based Library and Information Practice · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicImpact of AI and Big Data on Business and Society
Canadian institutionsnot available
Fundersnot available
KeywordsCitationLibrary scienceComputer scienceWorld Wide WebTollOpen access journalScientometricsScopusPolitical scienceMEDLINEMedicineLaw

Abstract

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A Review of:
 Sotudeh, H., Ghasempour, Z., & Yaghtin, M. (2015). The citation advantage of author-pays model: The case of Springer and Elsevier OA journals. Scientometrics, 104(2), 581-608. http://dx.doi.org/10.1007/s11192-015-1607-5 
 
 Abstract
 
 Objective – To investigate the citation performance of open access (OA) and toll access (TA) papers published in author-pays open access journals.
 
 Design – Longitudinal citation analysis.
 
 Setting – Publications in Springer and Elsevier’s author-pays open access journals.
 
 Subjects – 633 journals published using the author-pays model. This model encompasses both journals where the article processing charge (APC) is required and journals in which authors can request open access and voluntarily pay APCs for accepted manuscripts.
 
 Methods – The authors identified APC funded journals (journals funded by mandatory author processing charges as well as those where authors voluntarily paid a fee in order to have their articles openly accessible) from both Springer and Elsevier, and analyzed papers published in these journals from 2007 to 2011. The authors excluded journals that adopted the APC model later than 2007. To identify Springer titles, the authors created a search strategy to identify open access articles in SpringerLink. A total of 576 journals were identified and double checked in the Sherpa-Romeo database (a database of copyright and open access self-archiving policies of academic journals) to verify their open access policies. The authors then downloaded the journal content using SpringerLink, and using Springer Author-Mapper, separated out the open access articles from the toll access articles. 
 
 In order to identify the Elsevier APC funded journals, the authors referred to “Open Access Journal Directory: A-Z,” which contained 35 OA journals (p. 584). Once the authors consulted “Sponsored articles” issued by Elsevier and verified titles in Sherpa-Romeo, they identified 57 journals that fit the “author-pays” model. The bibliographic information was downloaded and OA articles were separated from TA articles. The authors confirmed that all journals were indeed OA publications by downloading the full-text from off-campus locations; they also verified that the journals were using the APC model by visiting each journal’s website. 
 
 Because of the large number of subject areas of the identified journals, the researchers decided to classify the journals into four broader categories: Health Sciences, Life Sciences, Natural Sciences, and Social Sciences and Humanities. To calculate the impact of OA papers, citation per paper (CPP) was calculated for each subject area. Impact values were calculated on an annual basis as well. The researchers calculated the citation advantage of OA articles as the “difference between the open access and toll access impacts in terms of a percentage of the latter” (p. 585).
 
 Main Results – The authors categorized their findings according to three themes: the growth of APC funded OA papers, the number of OA papers by discipline, and citation advantage of OA vs. TA in general and by subject area.
 
 Together, Springer and Elsevier published 18,654 OA papers in the APC journals; this number represents 4.7% of the 396,760 papers published between 2007 and 2011. While the number of OA and TA papers has been growing annually, the number of OA papers has been growing more rapidly compared to the TA papers. 
 
 In terms of subject areas, Life Sciences had the largest number of OA and TA papers (184,315), followed by Health Sciences (149,341), Natural Sciences (121,274), and Social Sciences and Humanities (42,824). Natural Sciences had the most OA papers (5.7%) in terms of the number of papers in this subject area being OA papers, followed by Social Sciences and Humanities (5.2%), Health Sciences (4.6%) and Life Sciences (3.6%). 
 
 Overall, the researchers found that the impact values of OA papers were larger than those of the TA papers for each year examined. In considering subject areas, in all disciplines except Life Sciences, the most highly cited paper in the field is an OA paper. In Life Sciences, the most highly cited TA paper had 2,215 citations, compared to the OA paper, which had 1,501 citations. Even though the TA paper had more citations, overall, the OA papers had a higher impact (citation advantage). In Health Sciences, the most highly cited OA paper received 1,501 citations, which is 1.2 times the most highly cited TA paper, with 1,252 citations. The citation advantage for the OA group is 33.29% higher than the TA group. In Natural Sciences, the number of citations from the highest cited OA paper is 1,736, or 2.52 times higher than the most highly cited TA paper. The OA papers in this discipline had a 35.95% citation advantage. In Social Sciences and Humanities, the most highly cited OA paper had 681 citations, compared to the TA paper, with 432 citations. For this subject area, the citation impact of the OA paper is 3.14% higher than the TA paper. 
 
 Conclusions – In sum, the number of article processing charge funded open access papers has grown tremendously in recent years. Furthermore, open access papers have a citation advantage over toll access papers, both annually and across disciplines.

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)0.006
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.716
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0310.535
Open science0.0050.003
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 head0.274
GPT teacher head0.486
Teacher spread0.212 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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