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Record W1564712492 · doi:10.18438/b8c88z

Open Access Articles Have a Greater Research Impact Than Articles Not Freely Available

2006· article· en· W1564712492 on OpenAlexvenueno aff
Suzanne Lewis

Bibliographic record

VenueEvidence Based Library and Information Practice · 2006
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsCitationWeb of scienceComputer scienceCitation analysisSample (material)PopulationCitation impactLibrary scienceWorld Wide WebMEDLINESociologyPolitical scienceDemography

Abstract

fetched live from OpenAlex

A review of: Antelman, Kristin. “Do Open-Access Articles Have a Greater Research Impact?” College & Research Libraries 65.5 (Sep. 2004): 372-82. Objective – To ascertain whether open access articles have a greater research impact than articles not freely available, as measured by citations in the ISI Web of Science database. Design – Analysis of mean citation rates of a sample population of journal articles across four disciplines. Setting – Journal literature across the disciplines of philosophy, political science, mathematics, and electrical and electronic engineering. Subjects – A sample of 2,017 articles across the four disciplines published between 2001 and 2002 (for political science, mathematics, and electrical and electronic engineering) and between 1999 and 2000 (for philosophy). Methods – A systematic presample of articles for each of the disciplines was taken to calculate the necessary sample sizes. Based on this calculation, articles were sourced from ten leading journals in each discipline. The leading journals in political science, mathematics, and electrical and electronic engineering were defined by ISI’s Journal Citation Reports for 2002. The ten leading philosophy journals were selected using a combination of other methods. Once the sample population had been identified, each article title and the number of citations to each article (in the ISI Web of Science database) were recorded. Then the article title was searched in Google and if any freely available full text version was found, the article was classified as open access. The mean citation rate for open access and non-open access articles in each discipline was identified, and the percentage difference between the means was calculated. Main results – The four disciplines represented a range of open access uptake: 17% of articles in philosophy were open access, 29% in political science, 37% in electrical and electronic engineering, and 69% in mathematics. There was a significant difference in the mean citation rates for open access articles and non-open access articles in all four disciplines. The percentage difference in means was 45% in philosophy, 51% in electrical and electronic engineering, 86% in political science, and 91% in mathematics. Mathematics had the highest rate of open access availability of articles, but political science had the greatest difference in mean citation rates, suggesting there are other, discipline-specific factors apart from rate of open access uptake affecting research impact. Conclusion – The finding that, across these four disciplines, open access articles have a greater research impact than non-open access articles, is only one aspect of the complex changes that are presently taking place in scholarly publishing and communication. However, it is useful information for librarians formulating strategies for building institutional repositories, or exploring open access publishing with patrons or publishers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.028
metaresearch head score (Gemma)0.163
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.163
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0300.037
Science and technology studies0.0020.004
Scholarly communication0.0200.017
Open science0.0010.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0310.007

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 head0.666
GPT teacher head0.593
Teacher spread0.073 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
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

Citations4
Published2006
Admission routes1
Has abstractyes

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