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Record W4391607910 · doi:10.1080/10508422.2024.2306134

Bibliometric review and mapping analysis of publication ethics research

2024· article· en· W4391607910 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEthics & Behavior · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsScientific misconductOriginalityPublishingMisconductBibliometricsResearch ethicsEngineering ethicsPolitical scienceIntellectual propertyResearch integritySocial scienceLibrary scienceSociologyPublic relationsMedicineLawAlternative medicineEngineeringComputer scienceQualitative research

Abstract

fetched live from OpenAlex

Publication ethics aim to protect intellectual property rights, ensure the originality of research work, and avoid plagiarism, including self-plagiarism. This study employed bibliometric methods to systematically research the field of publication ethics from 1972–2022; 659 articles on publication ethics were identified. This study included 1336 authors from 762 institutions in 67 countries. Publication ethics in biomedical journals are receiving increasing attention. Misconduct in scientific publishing remains a prominent theme, indicating ongoing development in the field. The literature highlights current research trends and emphasizes the need for increased collaboration among countries, authors, and institutions to enhance the quality and efficiency of research.

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.

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)0.051
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics, Research integrity
Consensus categoriesMetaresearch, Bibliometrics, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0510.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0240.146
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.009
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 head0.404
GPT teacher head0.552
Teacher spread0.148 · 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