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Publications

Publications is an international, peer-reviewed, open access journal on scholarly publishing, published quarterly online by MDPI.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, ESCI (Web of Science), RePEc, dblp, and other databases.
Journal Rank: JCR - Q2 (Information Science and Library Science) / CiteScore - Q1 (Communication)
Open Peer-Review: authors have the option for all reviewer comments and editorial decisions to be published along with the final paper. For more, see: Editorial, Paper with Review Comments.
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 27.4 days after submission; acceptance to publication is undertaken in 4.8 days (median values for papers published in this journal in the second half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.

Impact Factor: 2.5 (2024); 5-Year Impact Factor: 3.7 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2304-6775

Latest Articles

16 pages, 891 KB

Open AccessArticle

Supporting the University Research Enterprise via Open Access Publishing: Case Study from a Carnegie Research 2 University

by Rachel Elizabeth Scott

Publications 2026, 14(1), 10; https://doi.org/10.3390/publications14010010 - 5 Feb 2026

Academic libraries support the mission and vision of their institution; in the case of most universities, this means providing a variety of services and resources in support of the research enterprise. This case study documents one library’s support for open access publishing to [...] Read more.

Academic libraries support the mission and vision of their institution; in the case of most universities, this means providing a variety of services and resources in support of the research enterprise. This case study documents one library’s support for open access publishing to explore how it directly supports the research mission of a Carnegie Research 2 university. By leveraging relationships and investing existing collections resources and workflows—the sequence of decisions and labor through which librarians make scholarly and artistic works discoverable, accessible, and support their preservation—in open access publishing, the library has materially increased the visibility of locally produced scholarship and become a more visible campus collaborator. Full article

(This article belongs to the Special Issue Academic Libraries in Supporting Research)

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9 pages, 176 KB

Open AccessEssay

Interpreting Bibliometric Indicators as the “Blood Tests” of Research Systems

by Tindaro Cicero

Publications 2026, 14(1), 9; https://doi.org/10.3390/publications14010009 - 28 Jan 2026

The increasing emphasis on responsible research assessment has renewed the need for conceptual tools that help communicate the complementary roles of quantitative and qualitative evaluation. This essay proposes an interpretative metaphor that frames bibliometric indicators as the “blood tests” of research systems—heuristic devices [...] Read more.

The increasing emphasis on responsible research assessment has renewed the need for conceptual tools that help communicate the complementary roles of quantitative and qualitative evaluation. This essay proposes an interpretative metaphor that frames bibliometric indicators as the “blood tests” of research systems—heuristic devices that reveal multidimensional aspects of system vitality, balance, and dysfunction. The metaphor, grounded in standard categories of clinical diagnostics (hematological, hepatic, renal, lipidic, and cardiovascular panels), provides an accessible language for scholars and policymakers in research. Each bibliometric technique—ranging from publication and citation counts to patent analysis, altmetrics, and topic modelling—is associated with a diagnostic function such as screening, monitoring, or early risk detection. By linking established principles of responsible metrics (DORA, Leiden Manifesto, Metric Tide, CoARA) with the professionalization of evaluators, the essay situates the metaphor within current debates on bibliometric literacy and the ethical interpretation of indicators. Rather than prescribing metrics or decision rules, the contribution invites reflection on how evaluators can interpret bibliometric signals diagnostically—as contextual evidence for institutional learning, strategic decision-making, and the cultivation of healthy, adaptive research systems. Consistent with the essay format, this contribution does not propose a new evaluative methodology nor empirical validation. Instead, it advances a heuristic and communicative framework intended to emphasize the holistic, contextual, and professionally informed interpretation of quantitative indicators in the evaluation of research activity. Full article

18 pages, 1651 KB

Open AccessArticle

The Penetration of Digital Methods into Historical Scholarship: A Text-Mining Analysis of Russian Publications

by Zinaida Sokova, Valery Kruzhinov and Anna Glazkova

Publications 2026, 14(1), 8; https://doi.org/10.3390/publications14010008 - 20 Jan 2026

The integration of digital technologies into historical research is a global trend; however, its manifestation varies across national academic traditions. This study investigates the explicit articulation and terminological adoption of digital methods in Russian historical science by analyzing the prevalence and dynamics of [...] Read more.

The integration of digital technologies into historical research is a global trend; however, its manifestation varies across national academic traditions. This study investigates the explicit articulation and terminological adoption of digital methods in Russian historical science by analyzing the prevalence and dynamics of specific technological terms in a large corpus of publications. We first constructed a controlled thesaurus of 166 digital technologies by manually curating keyphrases from Russia’s primary specialized journal in the field (“Istoricheskaya Informatika”, Historical Informatics). This vocabulary was then used to perform text-mining on two distinct corpora: a broad sample of 95K Russian-language history articles from various journals (2004–2024) and a focused sample of publications on the Great Patriotic War History from the Russian Science Citation Index (RSCI, 2014–2023). Our quantitative analysis reveals the frequency, trends, and thematic context of digital method mentions. The findings highlight a significant disparity between the specialized discourse of “Istoricheskaya Informatika” and the mainstream historical publications, while also identifying specific areas (such as archaeological studies) where certain technologies have gained traction. This research offers a novel, data-driven perspective on the “digital turn” in Russian historiography and contributes to the comparative study of digital humanities’ global development. Full article

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7 pages, 307 KB

Open AccessEditorial

Seeds Not Trophies: Reflections on a Scholarly Life of Publications

by Chee Kong Yap

Publications 2026, 14(1), 7; https://doi.org/10.3390/publications14010007 - 9 Jan 2026

In 2003, as a young lecturer, I saw research as a craft to be learned, not a tally to be scored [...] Full article

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13 pages, 275 KB

Open AccessEssay

Reviewing Crowdsourcing and Community Engagement in Museums

by Paul Longley Arthur, Lydia Hearn and Isabel Smith

Publications 2026, 14(1), 6; https://doi.org/10.3390/publications14010006 - 5 Jan 2026

Over the past two decades, museums have increasingly experimented with digital technologies to connect with broader contemporary culture. This review article investigates the role crowdsourcing can play in transforming museums into more engaged environments, raising visibility and inclusivity, and involving diverse voices and [...] Read more.

Over the past two decades, museums have increasingly experimented with digital technologies to connect with broader contemporary culture. This review article investigates the role crowdsourcing can play in transforming museums into more engaged environments, raising visibility and inclusivity, and involving diverse voices and populations in knowledge-creation processes. Its contribution is to provide an overview of the history, definitions and concepts of crowdsourcing, and examples of crowdsourcing policies and practices that have been adopted by museums. Participation in crowdsourcing has been influenced by gender, education, and socio-economic and cultural background. In the past, historical structures and traditions and infrastructural complexities have stood in the way of wider diversity and inclusivity. As museums move increasingly online, the circulation of information outside the museum’s walls is just as important as the specialist knowledge held within. Museums can play a leading role in public communication by reaching those who constitute the ‘crowd’. This paper explores how museums, through strong collaboration and various forms of crowdsourcing, such as citizen science and participatory engagement, can offer more wide-ranging open access for the sharing and democratisation of knowledge. Full article

32 pages, 2901 KB

Open AccessArticle

A Hybrid BWM-GRA-PROMETHEE Framework for Ranking Universities Based on Scientometric Indicators

by Dedy Kurniadi, Rahmat Gernowo and Bayu Surarso

Publications 2026, 14(1), 5; https://doi.org/10.3390/publications14010005 - 4 Jan 2026

University rankings based on scientometric indicators frequently rely on compensatory aggregation models that allow extreme values to dominate the evaluation, while also remaining sensitive to outliers and unstable weighting procedures. These issues reduce the reliability and interpretability of the resulting rankings. This study [...] Read more.

University rankings based on scientometric indicators frequently rely on compensatory aggregation models that allow extreme values to dominate the evaluation, while also remaining sensitive to outliers and unstable weighting procedures. These issues reduce the reliability and interpretability of the resulting rankings. This study proposes a hybrid BWM–GRA–PROMETHEE (BGP) framework that combines judgement-based weighting Best-Worst Method (BWM), outlier-resistant normalization Grey Relational Analysis (GRA), and a non-compensatory outranking method Preference Ranking Organization Methods for Enrichment Evaluation (PROMETHEE II). The framework is applied to an expert-validated set of scientometric indicators to generate more stable and behaviorally grounded rankings. The results show that the proposed method maintains stability under weight and threshold variations and preserves ranking consistency even under outlier-contaminated scenarios. Comparative experiments further demonstrate that BGP is more robust than Additive Ratio Assesment (ARAS), Multi-Attributive Border Approximation Area Comparison (MABAC), and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), achieving the highest Spearman. This study contributes a unified evaluation framework that jointly addresses three major methodological challenges in scientometric ranking, outlier sensitivity, compensatory effects, and instability from data-dependent weighting. By resolving these issues within a single integrated model, the proposed BGP approach offers a more reliable and methodologically rigorous foundation for researchers and policymakers seeking to evaluate and enhance research performance. Full article

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9 pages, 374 KB

Open AccessCommentary

The Newcastle–Ottawa Scale for Assessing the Quality of Studies in Systematic Reviews

by Emanuela Gualdi-Russo and Luciana Zaccagni

Publications 2026, 14(1), 4; https://doi.org/10.3390/publications14010004 - 1 Jan 2026

Cited by 4

Secondary research is a cornerstone of health sciences, with substantial implications for clinical practice and health policy. Within the systematic review process, a key step is assessing study quality and risk of bias. Among the tools available for evaluating observational studies, the Newcastle–Ottawa [...] Read more.

Secondary research is a cornerstone of health sciences, with substantial implications for clinical practice and health policy. Within the systematic review process, a key step is assessing study quality and risk of bias. Among the tools available for evaluating observational studies, the Newcastle–Ottawa Scale (NOS) holds a prominent position and is widely applied in medical research. However, ambiguities and excessive subjectivity have been noted in its application. In this commentary, we discuss the Newcastle–Ottawa Scale guidelines, providing illustrative examples and practical recommendations for completing its items. Improving the accuracy of risk-of-bias assessment is crucial for enhancing the reliability of data synthesis and interpretation in the health sciences. Full article

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17 pages, 2690 KB

Open AccessArticle

Academic Libraries as Partners in Data Literacy Education—An Explorative Case Study

by Simone Fühles-Ubach, Elisabeth Kaliva and Martina Echtenbruck

Publications 2026, 14(1), 3; https://doi.org/10.3390/publications14010003 - 1 Jan 2026

The concept of the ‘teaching library’, which originated in the Anglo-American world, describes all activities of libraries in the field of promoting information, media, and data literacy, as well as other skills in dealing with analog and digital media. Although data literacy is [...] Read more.

The concept of the ‘teaching library’, which originated in the Anglo-American world, describes all activities of libraries in the field of promoting information, media, and data literacy, as well as other skills in dealing with analog and digital media. Although data literacy is explicitly mentioned in this definition, many training courses in academic libraries seem to focus more on promoting library use, information, and media literacy. Given that the creation of data management plans, along with the indexing, storage, and reuse of research data, have become standard elements of the research process, this article discusses the growing importance of academic libraries in teaching data literacy. It presents a modular course framework, developed in exchange with the university library, as a reusable model for data literacy education. The primary objective is to introduce this framework and illustrate its application; preliminary, exploratory insights from a self-assessment survey are provided to support this presentation. The limited participant count in the pre- and post-evaluations restricts the statistical generalizability of the findings but provides a solid empirical impression of the effectiveness of the course format. Results indicate substantial learning progress in fields where academic libraries have proven expertise. The main conclusion is that such library-integrated interdisciplinary courses provide a valuable framework for data literacy education and highlight strategic areas for library involvement. Full article

(This article belongs to the Special Issue Academic Libraries in Supporting Research)

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16 pages, 604 KB

Open AccessArticle

Editorial Predictors of the Discontinuation of Open Access Scientific Journals in Scopus: An Analysis from DOAJ

by Jean Paul Simon Castillo-Nuñez, Carlos Alberto Minchon-Medina, Angie Clemente-Vega, Nohelia Rosa Vallenas-Aroni, Marile Lozano-Lozano and Myriam Báez-Sepúlveda

Publications 2026, 14(1), 2; https://doi.org/10.3390/publications14010002 - 1 Jan 2026

Open access (OA) has expanded scholarly publishing, yet concerns remain about the sustainability of journals indexed in selective databases. This study analyzes editorial predictors of discontinuation among 8730 journals simultaneously registered in the Directory of Open Access Journals (DOAJ) and indexed in Scopus, [...] Read more.

Open access (OA) has expanded scholarly publishing, yet concerns remain about the sustainability of journals indexed in selective databases. This study analyzes editorial predictors of discontinuation among 8730 journals simultaneously registered in the Directory of Open Access Journals (DOAJ) and indexed in Scopus, including 58 (0.66%) discontinued titles as of June 2025 (latest available update at the time of data extraction). The analyses revealed that a journal’s history of prior discontinuation was the strongest and most consistent predictor of future instability, confirming that discontinuation follows a path-dependent pattern rather than isolated events. Financial structure also played a decisive role: journals applying other editorial fees beyond standard article processing charges (APCs) were nearly four times more likely to experience discontinuation (IRR = 3.877, p = 0.048), while those following standardized APC models showed a protective but non-significant tendency (IRR = 0.378, p = 0.084). Journal age exhibited a modest yet significant positive effect (IRR = 1.032, p = 0.031), suggesting that older titles face a gradual accumulation of risk over time. By contrast, editorial practices such as plagiarism detection, waiver policies, and turnaround time showed no significant association. Overall, the findings indicate that discontinuation in Scopus-indexed OA journals is statistically associated with historical trajectories, financial transparency, and governance capacity, rather than by routine editorial procedures. Full article

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29 pages, 3634 KB

Open AccessArticle

Human–AI Complementarity in Peer Review: Empirical Analysis of PeerJ Data and Design of an Efficient Collaborative Review Framework

by Zhihe Yang, Xiaoyu Zhou, Yuxin Jiang, Xinjie Zhang, Qihui Gao, Yanzhu Lu and Anqi Yang

Publications 2026, 14(1), 1; https://doi.org/10.3390/publications14010001 - 19 Dec 2025

In response to the persistent imbalance between the rapid expansion of scholarly publishing and the constrained availability of qualified reviewers, an empirical investigation was conducted to examine the feasibility and boundary conditions of employing Large Language Models (LLMs) in journal peer review. A [...] Read more.

In response to the persistent imbalance between the rapid expansion of scholarly publishing and the constrained availability of qualified reviewers, an empirical investigation was conducted to examine the feasibility and boundary conditions of employing Large Language Models (LLMs) in journal peer review. A parallel corpus of 493 pairs of human expert reviews and GPT-4o-generated reviews was constructed from the open peer-review platform PeerJ Computer Science. Analytical techniques, including keyword co-occurrence analysis, sentiment and subjectivity assessment, syntactic complexity measurement, and n-gram distributional entropy analysis, were applied to compare cognitive patterns, evaluative tendencies, and thematic coverage between human and AI reviewers. The results indicate that human and AI reviews exhibit complementary functional orientations. Human reviewers were observed to provide integrative and socially contextualized evaluations, while AI reviews emphasized structural verification and internal consistency, especially regarding the correspondence between abstracts and main texts. Contrary to the assumption of excessive leniency, GPT-4o-generated reviews demonstrated higher critical density and functional rigor, maintaining substantial topical alignment with human feedback. Based on these findings, a collaborative human–AI review framework is proposed, in which AI systems are positioned as analytical assistants that conduct structured verification prior to expert evaluation. Such integration is expected to enhance the efficiency, consistency, and transparency of the peer-review process and to promote the sustainable development of scholarly communication. Full article

(This article belongs to the Special Issue AI in Academic Metrics and Impact Analysis)

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29 pages, 4365 KB

Open AccessArticle

A Multidisciplinary Bibliometric Analysis of Differences and Commonalities Between GenAI in Science

by Kacper Sieciński and Marian Oliński

Publications 2025, 13(4), 67; https://doi.org/10.3390/publications13040067 - 11 Dec 2025

Generative artificial intelligence (GenAI) is rapidly permeating research practices, yet knowledge about its use and topical profile remains fragmented across tools and disciplines. In this study, we present a cross-disciplinary map of GenAI research based on the Web of Science Core Collection (as [...] Read more.

Generative artificial intelligence (GenAI) is rapidly permeating research practices, yet knowledge about its use and topical profile remains fragmented across tools and disciplines. In this study, we present a cross-disciplinary map of GenAI research based on the Web of Science Core Collection (as of 4 November 2025) for the ten tool lines with the largest number of publications. We employed a transparent query protocol in the Title (TI) and Topic (TS) fields, using Boolean and proximity operators together with brand-specific exclusion lists. Thematic similarity was estimated with the Jaccard index for the Top–50, Top–100, and Top–200 sets. In parallel, we computed volume and citation metrics using Python and reconstructed a country-level co-authorship network. The corpus comprises 14,418 deduplicated publications. A strong concentration is evident around ChatGPT, which accounts for approximately 80.6% of the total. The year 2025 shows a marked increase in output across all lines. The Jaccard matrices reveal two stable clusters: general-purpose tools (ChatGPT, Gemini, Claude, Copilot) and open-source/developer-led lines (LLaMA, Mistral, Qwen, DeepSeek). Perplexity serves as a bridge between the clusters, while Grok remains the most distinct. The co-authorship network exhibits a dual-core structure anchored in the United States and China. The study contributes to bibliometric research on GenAI by presenting a perspective that combines publication dynamics, citation structures, thematic profiles, and similarity matrices based on the Jaccard algorithm for different tool lines. In practice, it proposes a comparative framework that can help researchers and institutions match GenAI tools to disciplinary contexts and develop transparent, repeatable assessments of their use in scientific activities. Full article

(This article belongs to the Special Issue AI in Academic Metrics and Impact Analysis)

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18 pages, 2266 KB

Open AccessArticle

Measuring Group Performance Fairly: The h-Group, Homogeneity, and the α-Index

by Roberto da Silva, José Palazzo M. de Oliveira and Viviane Moreira

Publications 2025, 13(4), 66; https://doi.org/10.3390/publications13040066 - 11 Dec 2025

Ranking research groups plays a crucial role in various contexts, such as ensuring the fair allocation of research grants, assigning projects, and evaluating journal editorial boards. In this paper, we analyze the distribution of h-indexes within research groups and propose a single metric [...] Read more.

Ranking research groups plays a crucial role in various contexts, such as ensuring the fair allocation of research grants, assigning projects, and evaluating journal editorial boards. In this paper, we analyze the distribution of h-indexes within research groups and propose a single metric to quantify their overall performance, termed the α-index. This index integrates two complementary aspects: the homogeneity of members’ h-indexes, captured by the Gini coefficient (g), and the h-group, an extension of the individual h-index to groups. By combining both uniformity and collective research output, the α-index provides a consistent and equitable metric for comparative evaluation, essentially calculated as the average relative h-group multiplied by

(1 - g)

and normalized by the maximum value of this quantity across all analyzed groups. We describe the full procedure for computing the index and its components and illustrate its application to computer science conferences, where program committees are compared through a resampling procedure that ensures fair comparisons across groups of different sizes. Additional results are presented for postgraduate programs, further demonstrating the method’s applicability. Correlation analyses are used to establish rankings; however, our primary goal is to recommend a fairer index that reduces deviations from those currently used by governmental agencies to evaluate conferences and graduate programs. The proposed approach offers a more nuanced assessment than simply averaging members’ h-indexes and can be applied broadly–for example, to university departments and research councils–contributing to a more equitable distribution of research funding, an issue of increasing importance. Full article

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12 pages, 251 KB

Open AccessPerspective

Regaining Scientific Authority in a Post-Truth Landscape

by Andrew M. Petzold and Marcia D. Nichols

Publications 2025, 13(4), 65; https://doi.org/10.3390/publications13040065 - 9 Dec 2025

Recent decades have seen a rise of anti-science rhetoric, fueled by scientific scandals and failures of peer review, and the rise of trainable generative AI spreading misinformation. We argue, moreover, that the continued erosion of scientific authority also arises from inherent features in [...] Read more.

Recent decades have seen a rise of anti-science rhetoric, fueled by scientific scandals and failures of peer review, and the rise of trainable generative AI spreading misinformation. We argue, moreover, that the continued erosion of scientific authority also arises from inherent features in science and academia, including a reliance on publication as a method for gaining professional credibility and success. Addressing this multifaceted challenge necessitates a concerted effort across several key areas: strengthening scientific messaging, combating misinformation, rebuilding trust in scientific authority, and fundamentally rethinking academic professional norms. Taking these steps will require widespread effort, but if we want to rebuild trust with the public, we must make significant and structural changes to the production and dissemination of science. Full article

(This article belongs to the Special Issue What Does the Anti-Science Trend Mean for Scholarly Publishing)

24 pages, 603 KB

Open AccessArticle

Exploring the Citation and Impact Advantages of Open Access Papers in Hybrid Journals: A Case Study of Biochemistry Publications

by Qiuyu Zhu, Jing Li, Yifei Chen, Yuqing Zhang, Jing Li and Junren Ming

Publications 2025, 13(4), 64; https://doi.org/10.3390/publications13040064 - 5 Dec 2025

Open Access (OA) has emerged as a pivotal driver shaping the dissemination scope and academic impact of research findings. To clarify the impact of publishing models such as open access on the citation performance of biochemical papers, this study selects 177,745 biochemistry professional [...] Read more.

Open Access (OA) has emerged as a pivotal driver shaping the dissemination scope and academic impact of research findings. To clarify the impact of publishing models such as open access on the citation performance of biochemical papers, this study selects 177,745 biochemistry professional papers included in the core collection of the Web of Science (WoS CC) as the research data; we conduct an analysis of citation and impact advantages in biochemistry research. Employing correlation analysis, baseline regression modeling, and two-way ANOVA, our analysis indicates that: OA publications in biochemistry exhibit notable citation and impact advantages, which are positively correlated with the degree of openness, and the key determinants of the OA advantage encompass funding sources, reference count, and publication region. At present, China accounts for a disproportionately small proportion of OA papers in this field. In the context of the open-science paradigm, Chinese academic journals must systematically address their developmental bottlenecks and formulate publication innovation strategies to enhance the quality of academic publishing. Full article

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8 pages, 208 KB

Open AccessReview

The Epistemic Downside of Using LLM-Based Generative AI in Academic Writing

by Bor Luen Tang

Publications 2025, 13(4), 63; https://doi.org/10.3390/publications13040063 - 1 Dec 2025

There is now widespread use of large language (LLM)-based generative artificial intelligence (AI) tools in academic research and writing. While these are convenient, quick, and output enhancing, they also arguably incur ethical issues, such as questionable authenticity and plagiarism. Here, I explore epistemological [...] Read more.

There is now widespread use of large language (LLM)-based generative artificial intelligence (AI) tools in academic research and writing. While these are convenient, quick, and output enhancing, they also arguably incur ethical issues, such as questionable authenticity and plagiarism. Here, I explore epistemological aspects of AI use in academic writing and posit that there is evidence for three related pitfalls in AI use that should not be ignored. These include (1) epistemic detriment or harm in terms of illusions of understanding, (2) potential for cognitive dulling or impairment, and (3) AI dependency (both habitual and/or emotional). Thus, any potential infringements of academic ethics aside, AI use in academic writing incurs intrinsic problems that are epistemic in nature. These epistemic downsides call for restraint and moderation beyond regulatory measures to address ethical issues in AI use. Full article

23 pages, 1583 KB

Open AccessArticle

Bias in Citation Visibility: Temporal Dynamics and the Unequal Life Cycle of Academic Articles—Evidence from SME and Internationalization Research

by Reyner Pérez-Campdesuñer, Alexander Sánchez-Rodríguez, Rodobaldo Martínez-Vivar, Margarita De Miguel-Guzmán and Gelmar García-Vidal

Publications 2025, 13(4), 62; https://doi.org/10.3390/publications13040062 - 1 Dec 2025

This study analyzes the temporal evolution of citations received by academic articles in the field of micro, small, and medium-sized enterprises (SMEs) and internationalization processes, with the aim of identifying patterns of growth and decline in scientific visibility. Based on a dataset of [...] Read more.

This study analyzes the temporal evolution of citations received by academic articles in the field of micro, small, and medium-sized enterprises (SMEs) and internationalization processes, with the aim of identifying patterns of growth and decline in scientific visibility. Based on a dataset of 1936 articles retrieved from Scopus, we constructed an article–year panel that enabled the application of multiple statistical approaches. Discrete-time survival models showed that the annual probability of receiving at least one citation is initially low, increases slightly until the fifth year, and then declines progressively thereafter. Negative binomial regression confirmed significant growth during the first five years, followed by a slowdown. Kaplan–Meier estimations reinforced this finding by showing that the cumulative proportion of articles receiving their first citation within a decade remains limited. These results confirm that citation dynamics are nonlinear and subject to early obsolescence, with most visibility concentrated in the short term. Importantly, this temporal bias in indexing and evaluation systems disproportionately favors recent publications while undervaluing older but still influential research. Such structural bias has profound implications for visibility and equity in scholarly communication, especially for disciplines and regions where citation cycles are longer. The findings thus validate the study’s propositions: first, that citation growth slows significantly after the fifth year, and second, that this slowdown represents a structural bias that amplifies inequities in research evaluation. Full article

(This article belongs to the Special Issue Bias in Indexing: Effects on Visibility and Equity)

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24 pages, 325 KB

Open AccessArticle

Ethical Considerations for the Use of Artificial Intelligence in Linguistics Journal Publishing: Combining Hybrid Thematic Analysis and Critical Discourse Analysis

by Xuan Wang and Xinyi Zhang

Publications 2025, 13(4), 61; https://doi.org/10.3390/publications13040061 - 25 Nov 2025

The immense potential of artificial intelligence (AI) in academic journal publishing has significantly impacted scholarly communication between stakeholders, leading to increased research into ethical considerations for AI use in academic publishing. Due to the contextual nature of ethics and the ontological base of [...] Read more.

The immense potential of artificial intelligence (AI) in academic journal publishing has significantly impacted scholarly communication between stakeholders, leading to increased research into ethical considerations for AI use in academic publishing. Due to the contextual nature of ethics and the ontological base of language as its own object of inquiry, the conceptual framework and underlying ideologies of AI ethics in linguistics deserve attention. In this study, we address the call for these ethical considerations by combining a hybrid thematic analysis (HTA) of the ethical guidelines available on 144 Social Sciences Citation Index (SSCI) linguistics journals’ and 11 corresponding publishers’ websites as of 31 October 2025, and a critical discourse analysis (CDA) case study on Language Testing, a representative journal with self-developed AI ethical guidelines. Through the HTA, we identified seven themes: accountability, authorship, citation practices, copyright, long-term governance, human agency, and transparency. The role allocation of CDA demonstrated that the AI ethical guidelines independently established by the linguistics journal expand the scope of stakeholders to include the sources of research data and technology, covering the informed consent of research participants and the responsibilities of the AI tool operators. Moreover, AI tools are given a beneficialized role, suggesting a more technology-assisted-oriented perspective and reflecting deeper trust in AI’s involvement. Through the findings, our study contributes to the broader understanding of ethical governance in relation to AI usage in discipline-based communication, highlighting the need for a more dialogic and diverse framework to share responsibility among stakeholders to promote the ethical use of AI. Full article

13 pages, 481 KB

Open AccessArticle

Preserving Culinary Heritage Through AI: Sustainable Digitisation of Granny Josie’s Notebooks

by Karol Król, Maria Szkutak and Elżbieta Legutko

Publications 2025, 13(4), 60; https://doi.org/10.3390/publications13040060 - 20 Nov 2025

Granny Josie’s Notebooks are salvaged notebooks written in 1946–1947 during a rural domestic science course for girls. This study aims to extract historically valuable information on the culinary heritage of post-war Poland and the housekeeping role attributed to women, with a specific focus [...] Read more.

Granny Josie’s Notebooks are salvaged notebooks written in 1946–1947 during a rural domestic science course for girls. This study aims to extract historically valuable information on the culinary heritage of post-war Poland and the housekeeping role attributed to women, with a specific focus on assessing the performance of Large Language Models (LLMs) in corpus analysis. The research began with an inquiry into the historical context of the notebooks. Three notebooks were digitised and stored in data repositories, then converted into editable vector text. The corpus was analysed with AI, and the results were compared with a text profile prepared by qualified linguists. According to the AI, the texts’ characteristic features are descriptions of nearly ritual food preparation, serving, and table setting. Women appear as central figures in post-war Polish housekeeping, acting as guardians of the hearth and planners and preparers of meals. However, AI’s interpretations were often overly idealised, with embellished descriptions that did not fully reflect the actual text. The digitisation and analysis of Granny Josie’s Notebooks provided new information about the culinary heritage of post-war Poland and preserved these materials from oblivion, while offering insights into the potential application of LLMs in corpus analysis. Full article

(This article belongs to the Special Issue Digital Humanities and Ancient Manuscripts)

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24 pages, 3848 KB

Open AccessReview

An Assessment of Scientific Productivity: Review in the Area of Agricultural and Biological Sciences in Ecuador Using Scientometrics and Lotka’s Law

by William Viera-Arroyo, Lya Vera, Martín Moya, Duther López, Wilson Vásquez-Castillo and Carlos Caicedo

Publications 2025, 13(4), 59; https://doi.org/10.3390/publications13040059 - 19 Nov 2025

Scientific production is a key indicator of a country’s academic and institutional development. This review followed a quantitative and descriptive bibliometric design using Lotka’s Law, aimed at analysing Ecuador’s scientific production in the area of Agricultural and Biological Sciences from 2014 to 2024. [...] Read more.

Scientific production is a key indicator of a country’s academic and institutional development. This review followed a quantitative and descriptive bibliometric design using Lotka’s Law, aimed at analysing Ecuador’s scientific production in the area of Agricultural and Biological Sciences from 2014 to 2024. The bibliographic data were obtained from the Scopus database, which offers comprehensive coverage of the peer-reviewed literature and standardised metadata. Data (2881 documents) revealed publication patterns, collaboration networks and impact indicators. Lotka’s Law was applied to evaluate and describe author productivity among researchers affiliated with Ecuadorian universities and the Instituto Nacional de Investigaciones Agropecuarias (INIAP). The model yielded an average n-parameter of 2.56, indicating a moderate concentration among a small group of researchers. There was a sustained growth in scientific publications, especially after 2018, with a high proportion published in Q1 and Q2 journals. The institutions with the most relevant affiliations included PUCE, UTM, USFQ, INIAP, ESPOL and UDLA, all maintaining consistent contributions to scientific output. The keyword co-occurrence analysis revealed a thematic focus on biodiversity, taxonomy and conservation. The limitations of this study were related to the fact that the analysis was based only on data retrieved from the Scopus database and that the use of Lotka’s Law assumes a theoretical distribution that does not fully account for contextual factors. Overall, Ecuador’s scientific system shows progress in terms of research productivity; however, it requires further development and the strengthening of institutional and human research capacities to generate more equitable scientific production in terms of the number of researchers. Full article

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Open AccessArticle

Bibliometric Outlook on Economics and Business Research in Kazakhstan (2019–2023)

by Diana Amirbekova, Targyn Nauryz, Mariyam Taskinbayeva, Madina Bigabatova and Aasso Ziro

Publications 2025, 13(4), 58; https://doi.org/10.3390/publications13040058 - 18 Nov 2025

This study examines the evolution of Kazakhstani research in the fields of economics and business research. We analyzed Scopus and Dimensions records for 2019–2023 following a PRISMA-like workflow with fully reproducible queries and time-stamped data extractions. We implemented both Bradford’s law of scattering [...] Read more.

This study examines the evolution of Kazakhstani research in the fields of economics and business research. We analyzed Scopus and Dimensions records for 2019–2023 following a PRISMA-like workflow with fully reproducible queries and time-stamped data extractions. We implemented both Bradford’s law of scattering and collaboration analysis. We report both journal-level (Scopus) and publication-level (Dimensions) results as complementary perspectives. Results show the applicability of Bradford’s law of scattering to research publications in Economics, Econometrics, and Finance, Business, Management, and Accounting, and Decision Sciences in Kazakhstan and globally. Collaboration analysis highlights strong regional ties and diversification. Authorship analysis reveals that 85.1% of publications have a Kazakhstan-affiliated first author. Publications were classified into three categories: Kazakhstan-Only (59.0%, N = 1585), International Collaboration with Kazakhstan-led authorship (31.5%, N = 845), and International Collaboration with Non-Kazakhstan-led authorship (9.5%, N = 255). International collaborations had 69–92% higher citation impact than domestic-only publications. The expansion of citing countries doubled in 2023 compared with 2019. Our contributions to bibliometric analysis and science policy are two-fold. First, we provide a comprehensive comparative analysis of publication patterns between Kazakhstani and global journals in economics and business-related fields, revealing specific areas requiring development. Second, we identify collaboration patterns, including citation analysis of studied fields. The analysis revealed strategies that can be applied in other emerging economies. Full article

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