Open Access APCs Are Already a Scam”: Knowledge and Opinions of Open Access and Article Processing Charges From Faculty at a Large Public University

Authors : Heidi M. Winkler

Introduction:

In the 2020s, open access (OA) continues to act as a challenging force in the ever-shifting landscape of scholarly communication. The objective of this study was to survey faculty at an R1 research institution about their perspectives on OA publishing, article processing charges (APCs), and knowledge of the institutional repository (IR).

Methods:

This study employed an anonymous online survey of 415 faculty members, with a response rate of 12.77% (53 responses). The survey collected both quantitative and qualitative data from respondents.

Results and Discussion:

Results showed engagement with OA publishing but skepticism of APCs as a reasonable alternative to subscription-based funding models. Survey respondents were also mostly unaware of the library’s IR self-archiving service.

Conclusion:

For-profit OA business models do not serve academics, and they and scholarly communications librarians should better collaborate to advocate for transitioning away from APCs. The article concludes by sharing how the author changed practice based on the results of the study.

URL : Open Access APCs Are Already a Scam”: Knowledge and Opinions of Open Access and Article Processing Charges From Faculty at a Large Public University

DOI : https://doi.org/10.31274/jlsc.17647

Enhancing Research Methodology and Academic Publishing: A Structured Framework for Quality and Integrity

Authors : Md. Jalil Piran, Nguyen H. Tran

Following a brief introduction to research, research processes, research types, papers, reviews, and evaluations, this paper presents a structured framework for addressing inconsistencies in research methodology, technical writing, quality assessment, and publication standards across academic disciplines. Using a four-dimensional evaluation model that focuses on 1) technical content, 2) structural coherence, 3) writing precision, and 4) ethical integrity, this framework not only standardizes review and publication processes but also serves as a practical guide for authors in preparing high-quality manuscripts. Each of these four dimensions cannot be compromised for the sake of another.

Following that, we discuss the components of a research paper adhering to the four-dimensional evaluation model in detail by providing guidelines and principles. By aligning manuscripts with journal standards, reducing review bias, and enhancing transparency, the framework contributes to more reliable and reproducible research results. Moreover, by strengthening cross-disciplinary credibility, improving publication consistency, and fostering public trust in academic literature, this initiative is expected to positively influence both research quality and scholarly publishing’s reputation.

Arxiv : https://arxiv.org/abs/2412.05683

Publication Trends in Artificial Intelligence Conferences: The Rise of Super Prolific Authors

Authors : Ariful Azad, Afeefa Banu

Papers published in top conferences contribute influential discoveries that are reshaping the landscape of modern Artificial Intelligence (AI). We analyzed 87,137 papers from 11 AI conferences to examine publication trends over the past decade. Our findings reveal a consistent increase in both the number of papers and authors, reflecting the growing interest in AI research.

We also observed a rise in prolific researchers who publish dozens of papers at the same conference each year. In light of this analysis, the AI research community should consider revisiting authorship policies, addressing equity concerns, and evaluating the workload of junior researchers to foster a more sustainable and inclusive research environment.

Arxiv : https://arxiv.org/abs/2412.07793

The roles of special issues in scholarly communication in a changing publishing landscape

Authors : Robyn M. GleasnerAkshay Sood

This paper aims to enhance the understanding of the role of special issues in the evolving landscape of academic publishing, offering insights for publishers, editors, guest editors, and researchers, including how new technologies influence transparency in publishing processes, open access models, and metrics for success.

Based upon original analysis, the paper also discusses the importance of special issues and opportunities to support diversity, equity, and inclusivity in special issue publishing programmes. The goal is to contribute to the discussion of maintaining research integrity through special issues, acknowledging their significance in scholarly communication, while offering suggestions for the future.

URL : The roles of special issues in scholarly communication in a changing publishing landscape

DOI : https://doi.org/10.1002/leap.1635

Essential work, invisible workers: The role of digital curation in COVID-19 Open Science

Authors : Irene V. PasquettoAmina A. AbduNatascha Chtena

In this paper, we examine the role digital curation practices and practitioners played in facilitating open science (OS) initiatives amid the COVID-19 pandemic. In Summer 2023, we conducted a content analysis of available information regarding 50 OS initiatives that emerged—or substantially shifted their focus—between 2020 and 2022 to address COVID-19 related challenges. Despite growing recognition of the value of digital curation for the organization, dissemination, and preservation of scientific knowledge, our study reveals that digital curatorial work often remains invisible in pandemic OS initiatives.

In particular, we find that, even among those initiatives that greatly invested in digital curation work, digital curation is seldom mentioned in mission statements, and little is known about the rationales behind curatorial choices and the individuals responsible for the implementation of curatorial strategies. Given the important yet persistent invisibility of digital curatorial work, we propose a shift in how we conceptualize digital curation from a practice that merely “adds value” to research outputs to a practice of knowledge production.

We conclude with reflections on how iSchools can lead in professionalizing the field and offer suggestions for initial steps in that direction.

URL : Essential work, invisible workers: The role of digital curation in COVID-19 Open Science

DOI : https://doi.org/10.1002/asi.24965

Open Science Alternatives to Scopus and the Web of Science: A Case Study in Regional Resilience

Authors : Irina D. Turgel, Olga A. Chernova

The recent years have seen increasing support for open science in academic circles. However, the large number of scientometric databases calls into question the comparability of the search and analysis tools they provide.

Using the subject area of regional resilience as an example, in this study, the aim was to analyze the capabilities of widely used databases to serve as alternatives to Scopus and Web of Science in solving research problems.

As alternatives, in the present article, the following open, free scientometric databases were considered: AMiner, Wizdom.ai, the Lens, Dimensions, and OpenAlex. Their capabilities were demonstrated for the subject area under study, and the obtained results were compared.

The study results showed that alternative databases provide essential data on trends in scientific development. It is noteworthy that they largely replicate the provided data, supplementing and expanding them by using different types of data sources. However, open databases do not guarantee a high quality of materials and exhibit a relatively low level of metadata.

Thus, it is premature to abandon the use of Scopus and Web of Science in research activities. Since scientometric databases were developed in different contexts, they are characterized by structural and functional heterogeneity, which complicates their comparison.

Therefore, a selective approach should be adopted for the choice of scientometric databases, taking into account financial and other constraints, as well as the specifics of research problems.

URL : Open Science Alternatives to Scopus and the Web of Science: A Case Study in Regional Resilience

DOI : https://doi.org/10.3390/publications12040043

Evaluating Research Quality with Large Language Models: An Analysis of ChatGPT’s Effectiveness with Different Settings and Inputs

Author : Mike Thelwall

Evaluating the quality of academic journal articles is a time consuming but critical task for national research evaluation exercises, appointments and promotion. It is therefore important to investigate whether Large Language Models (LLMs) can play a role in this process.

This article assesses which ChatGPT inputs (full text without tables, figures and references; title and abstract; title only) produce better quality score estimates, and the extent to which scores are affected by ChatGPT models and system prompts.

The results show that the optimal input is the article title and abstract, with average ChatGPT scores based on these (30 iterations on a dataset of 51 papers) correlating at 0.67 with human scores, the highest ever reported. ChatGPT 4o is slightly better than 3.5-turbo (0.66), and 4o-mini (0.66).

The results suggest that article full texts might confuse LLM research quality evaluations, even though complex system instructions for the task are more effective than simple ones.

Thus, whilst abstracts contain insufficient information for a thorough assessment of rigour, they may contain strong pointers about originality and significance. Finally, linear regression can be used to convert the model scores into the human scale scores, which is 31% more accurate than guessing.

Arxiv : https://arxiv.org/abs/2408.06752