Étiquette : authorship

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EN

Navigating the ethical landscape of scholarly publishing: a comparative evaluation of Gemini and DeepSeek LLMs in addressing authorship and contributorship disputes

Authors : Kannan Sridharan, Sivarama Krishnan

Background:

The rising complexity of publication ethics, particularly authorship disputes, necessitates exploring Large Language Models (LLMs) as potential evaluative tools. This study compares the performance of Google Gemini 2.5 Flash and DeepSeek-V3.2 against expert Committee on Publication Ethics (COPE) forum responses.

Methods:

A cross-sectional analysis including 12 COPE authorship and contributorship cases was conducted using three prompting strategies: Minimal, Deterministic, and Stochastic. Responses were scored across seven domains on a 5-point Likert scale (1 = poor, 5 = excellent) by independent raters.

Results:

Both LLMs achieved perfect scores (5 ± 0) in Actionability of Recommendations and high marks in Safety and Avoidance of Hallucination (4.88 ± 0.33). In the Consistency with COPE Principles domain, DeepSeek performed slightly better than Gemini (4.45 ± 1.0 vs. 4.12 ± 1.29), while Gemini showed a better Overall Appropriateness (4.03 ± 0.98 vs. 3.82 ± 1.29) but they were not statistically significant. Both models struggled most with Identification of Ethical Issues (Gemini: 3.91 ± 1.33; DeepSeek: 3.82 ± 1.29). Under Minimal prompts, Gemini’s ethical identification was lower (3.55 ± 1.44) compared to Deterministic/Stochastic prompts (4.09 ± 1.3). Qualitatively, Gemini recorded an 8% major disagreement rate with COPE, while DeepSeek had a 16% combined (minor and major) disagreement rate. Mean similarity scores to COPE forum experts were approximately 4 for both models. Both models missed specific legal/copyright nuances but provided unique “value-add” strategies, such as author disassociation statements and editorial de-escalation training, not present in original COPE forum advice.

Conclusion:

LLMs demonstrated high degree of alignment with COPE expert ethical reasoning. While they possess a “legal blind spot,” their ability to provide actionable and clear guidance, optimized through structured prompting, makes them valuable supplementary tools for journal editors.

URL : Navigating the ethical landscape of scholarly publishing: a comparative evaluation of Gemini and DeepSeek LLMs in addressing authorship and contributorship disputes

DOI : https://doi.org/10.3389/frma.2026.1781697

Catégories
EN

Generative artificial intelligence in the publishing industry: adoption, use, intellectual property, and other challenges

Author : Marco Giraldo-Barreto

Taking as a starting point how generative artificial intelligence (GenAI) works, this text explores the level of adoption of such technology in the publishing sector (in particular for Latin America), shows examples of legislation challenges faced by states and the publishing industry in terms of intellectual property, and the implications of GenAI misuse in the academic publishing context. Finally, it proposes a course of action for a responsible adoption for the publishing chain of value.

URL : Generative artificial intelligence in the publishing industry: adoption, use, intellectual property, and other challenges

DOI : https://doi.org/10.3389/frma.2026.1759242

Catégories
EN

Can ChatGPT write better scientific titles? A comparative evaluation of human-written and AI-generated titles

Authors : Paul Sebo, Bing Nie, Ting Wang

Background

Large language models (LLMs) such as GPT-4 are increasingly used in scientific writing, yet little is known about how AI-generated scientific titles are perceived by researchers in terms of quality.

Objective

To compare the perceived alignment with the abstract content (as a surrogate for perceived accuracy), appeal, and overall preference for AI-generated versus human-written scientific titles.

Methods

We conducted a blinded comparative study with 21 researchers from diverse academic backgrounds. A random sample of 50 original titles was selected from 10 high-impact general internal medicine journals. For each title, an alternative version was generated using GPT-4.0. Each rater evaluated 50 pairs of titles, each pair consisting of one original and one AI-generated version, without knowing the source of the titles or the purpose of the study.

For each pair, raters independently assessed both titles on perceived alignment with the abstract content and appeal, and indicated their overall preference. We analyzed alignment and appeal using Wilcoxon signed-rank tests and mixed-effects ordinal logistic regressions, preferences using McNemar’s test and mixed-effects logistic regression, and inter-rater agreement with Gwet’s AC.
Results

AI-generated titles received significantly higher ratings for both perceived alignment with the abstract content (mean 7.9 vs. 6.7, p-value <0.001) and appeal (mean 7.1 vs. 6.7, p-value <0.001) than human-written titles. The odds of preferring an AI-generated title were 1.7 times higher (p-value =0.001), with 61.8% of 1,049 paired judgments favoring the AI version. Inter-rater agreement was moderate to substantial (Gwet’s AC: 0.54–0.70).

Conclusions

AI-generated titles were rated more favorably than human-written titles within the context of this study in terms of perceived alignment with the abstract content, appeal, and preference, suggesting that LLMs may enhance the effectiveness of scientific communication. These findings support the responsible integration of AI tools in research.

URL : Can ChatGPT write better scientific titles? A comparative evaluation of human-written and AI-generated titles

DOI : https://doi.org/10.12688/f1000research.173647.2

Catégories
EN

On the potential value conflict between scientific knowledge production and fair recognition of authorship

Authors : Gert Helgesson, William Bülow

The value of scientific knowledge and fairness in distribution of academic credit are core values in research publication. However, it is little discussed in the literature that these values may come into conflict, particularly in interdisciplinary research. The point of this paper is to acknowledge and describe the conflict and discuss potential solutions.

We use collaborations between pre-clinical (laboratory) researchers and clinicians at hospitals as an exemplifying case. We conclude that, without changing the preconditions for the value conflict, there is no general solution involving systematically prioritizing one value over the other.

However, a potential way out of the conflict would be a general shift from authorship to contributorship regarding evaluation of contributions, but required routines are presently not in place with most journals.

URL : On the potential value conflict between scientific knowledge production and fair recognition of authorship

DOI : https://doi.org/10.1080/08989621.2026.2623480

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EN

Author Name Disambiguation in Scholarly Research: A Bibliometric Perspective

Authors : Hesham Amin Hamdy El Shamly, Subaveerapandiyan A.

The rapid expansion of scholarly publishing has amplified the long-standing challenge of author name ambiguity in academic databases. This issue, manifesting as homonymy and synonymy, undermines the accuracy of bibliometric analyses, author-level metrics, and research evaluation systems. Author Name Disambiguation (AND) has thus emerged as a critical focus area in digital scholarship, with evolving strategies ranging from supervised machine learning and graph-based models to the adoption of persistent digital identifiers like ORCID.

Despite notable advancements, significant challenges remain – particularly in linguistically diverse and underrepresented regions – where metadata inconsistencies, transliteration issues, and limited ORCID adoption exacerbate disambiguation errors. This study presents a comprehensive bibliometric analysis of 2,004 publications on AND from 2005 to 2024, sourced from the Scopus database.

Using tools such as Biblioshiny and VOSviewer, the analysis identifies publication trends, leading authors and institutions, core sources, co-authorship networks, and thematic evolution in the field. Findings highlight increasing international collaboration, the dominance of computer science-driven methodologies, and the critical role of metadata quality and institutional frameworks.

The study concludes with recommendations for inclusive, multilingual, and interoperable disambiguation systems, advocating for cross-disciplinary collaboration to ensure equitable author identification in global scholarly communication.

URL : Author Name Disambiguation in Scholarly Research: A Bibliometric Perspective

DOI : https://doi.org/10.1515/opis-2025-0035

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EN

Ethical and practical implications of AI in academic library research

Author : Nuno Sousa

This article offers a critical and integrative review of how artificial intelligence (AI) is being incorporated into academic library systems, particularly in the context of scientific research production. Based on 29 studies, the review explores ethical practices, institutional boundaries, and epistemological challenges surrounding AI adoption.

Findings reveal that AI is reshaping scholarly workflows, such as metadata creation, information retrieval, and literature review, while also introducing unresolved ethical concerns, including data privacy, algorithmic bias, academic integrity, and diminished human agency.

The study identifies a misalignment between the rapid pace of AI implementation and the capacity of academic institutions to regulate its use responsibly. Librarians are situated at the intersection of innovation and ethical mediation, often without formal training or institutional support.

The review concludes that AI should not be viewed merely as a functional tool but as a socio-technical agent requiring ethical governance, critical AI literacy, and structural accountability across academic ecosystems.

URL : Ethical and practical implications of AI in academic library research

DOI : https://doi.org/10.1177/03400352251391753

Catégories
EN

Shifting norms in scholarly publications: trends in readability, objectivity, authorship, and AI use

Authors : Padraig Cunningham, Padhraic Smyth, Barry Smyth

Academic and scientific publishing practices have changed significantly in recent years. This paper presents an analysis of 17 million research papers published since 2000 to explore changes in authorship and content practices. It shows a clear trend towards more authors, more references and longer abstracts.

While increased authorship has been reported elsewhere, the present analysis shows that it is pervasive across many major fields of study. We also identify a decline in author productivity which suggests that `gift’ authorship (the inclusion of authors who have not contributed significantly to a work) may be a significant factor. We further report on a tendency for authors to use more hyperbole, perhaps exaggerating their contributions to compete for the limited attention of reviewers, and often at the expense of readability.

This has been especially acute since 2023, as AI has been increasingly used across many fields of study, but particularly in fields such as Computer Science, Engineering and Business. In summary, many of these changes are causes of significant concern. Increased authorship counts and gift authorship have the potential to distort impact metrics such as field-weighted citation impact andh-index, while increased AI usage may compromise readability and objectivity.

DOI : https://doi.org/10.48550/arXiv.2510.21725