{"title":"A study of compliance with data-sharing requests by Social Science researchers.","authors":"Ashok Ghuge, Atul Patil, Rupali Khaire, Atul Kumar, Manesh Palav, Satish Warpade, Vinod Malkar, Amandeep Saini, Srinivasa Rao Kasisomayajula, Vishwas Pendse, Deepti Bhutada, Rajesh Gade, Rahul Dhaigude, Abhay Bora, Shirish Raibagkar","doi":"10.1080/08989621.2026.2723276","DOIUrl":"https://doi.org/10.1080/08989621.2026.2723276","url":null,"abstract":"<p><strong>Background: </strong>This paper examines responses to data-sharing requests from authors in the Social Sciences. Compliance with requests for data-sharing in Medical Sciences has been reported to be low. The study extends the scholarship by assessing compliance with similar requests in the Social Sciences.</p><p><strong>Methods: </strong>Four hundred empirical study authors from 400 Q1 Scopus-indexed Journals across eight prominent fields of the Social Sciences were requested to share the research data. Only those authors were contacted who had stated that data would be made available on request, or those who had not explicitly denied data-sharing.</p><p><strong>Results: </strong>Sixty-seven authors responded, of whom 15 (4%) provided data, while 52 declined to share data on grounds such as privacy concerns. The response rate of 4% was far lower than the average of 12% reported in Medical Sciences.</p><p><strong>Conclusions: </strong>While policy encourages data-sharing, practice has yet to catch up. Existing literature indicates various reasons for not sharing research data. These include unavailability, privacy concerns, ethical concerns, lack of publisher compulsion, and others. It is important to address the issue of authors not responding to requests despite a promise. Policymakers also need to examine this issue to identify ways to improve data-sharing and promote open science.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2723276"},"PeriodicalIF":4.4,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Radical reproducibility, real constraints: An autoethnography of open and transparent research from the inside.","authors":"Nicki Lisa Cole, Serge P J M Horbach","doi":"10.1080/08989621.2026.2721689","DOIUrl":"https://doi.org/10.1080/08989621.2026.2721689","url":null,"abstract":"<p><strong>Background: </strong>This paper presents a three-year longitudinal autoethnographic study of the TIER2 project, an international, interdisciplinary consortium committed to \"radical reproducibility\" through open research practices. We investigated how epistemic diversity, disciplinary norms, and institutional cultures shape reproducibility in practice.</p><p><strong>Methods/materials: </strong>We take an auto-ethnographic approach. Data include periodic consortium-wide surveys, quarterly reproducibility diaries by five diarists, and fieldnotes from General Assembly discussions; these were coded inductively.</p><p><strong>Results: </strong>We found that initial disciplinary differences in defining reproducibility evolved to a nuanced appreciation of its complexity. Participants developed new competencies in open research practices and experienced insights regarding early planning and collaborative transparency. Enablers of reproducibility include the Open Science Framework, co-developed tools, containerization, and \"slow science\" approaches, strong role modeling by senior researchers and improved documentation. Challenges include fear of exposing imperfect work, unequal engagement across career stages, and substantial time and resource demands. Epistemic tensions emerged around the applicability of reproducibility to qualitative research and the risk of standardization undermining diversity. Despite these, participants reported high professional satisfaction and intellectual growth.</p><p><strong>Conclusion: </strong>The study demonstrates that \"radical reproducibility\" is not merely a technical but a cultural and epistemic project that fosters collective learning, skill development and innovation, and requires systemic and institutional support.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2721689"},"PeriodicalIF":4.4,"publicationDate":"2026-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148814870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"When AI use becomes the norm: Researcher perspectives on AI disclosure policy and practice.","authors":"Ayoung Yoon, Siena Oristaglio","doi":"10.1080/08989621.2026.2716884","DOIUrl":"10.1080/08989621.2026.2716884","url":null,"abstract":"<p><strong>Background: </strong>Despite the proliferation of AI disclosure requirements in academic publishing, recent research suggests a persistent gap between policy expectations and research practice. However, little is known about how researchers perceive and navigate these requirements or what limitations they identify in current disclosure practices.</p><p><strong>Method: </strong>This study explored researchers' experiences with AI disclosure through semi-structured interviews with 14 researchers from two interdisciplinary fields, bioinformatics and computational social science. Data were analyzed using reflexive thematic analysis.</p><p><strong>Results: </strong>Four thematic groupings emerged: fragmented and inconsistently enforced requirements; systemic limitations, including scope ambiguity, research integrity risks, and structural disincentives to honest reporting; researcher perspectives on more effective disclosure practices; and disciplinary variation as a cross-cutting dimension shaping how these issues are experienced across research communities. The findings suggest that the compliance gap reflects an interaction between structural conditions and ethical obligations. This gap is sustained by self-reporting mechanisms that lack verification capacity, a transparency paradox in which honest disclosure can invite professional penalization, and disciplinary norms that resist uniform governance approaches.</p><p><strong>Conclusions: </strong>The study provides empirical evidence supporting the development of a structured AI contribution taxonomy as a more principled and practical alternative to existing disclosure practices. More broadly, the findings suggest that effective AI disclosure governance should incorporate field-sensitive adaptation rather than relying on uniform implementation across diverse research communities.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2716884"},"PeriodicalIF":4.4,"publicationDate":"2026-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148724091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoya Huang, Huiyu Luo, Julian Savulescu, Yonghui Ma
{"title":"The precautionary principle and the ethical governance of human brain organoid research.","authors":"Xiaoya Huang, Huiyu Luo, Julian Savulescu, Yonghui Ma","doi":"10.1080/08989621.2026.2717416","DOIUrl":"https://doi.org/10.1080/08989621.2026.2717416","url":null,"abstract":"<p><strong>Background: </strong>Human brain organoids have attracted increasing attention for their potential to model human brain development and neurological disorders. However, concerns about their possible consciousness have generated ongoing ethical debate. In situations where scientific evidence remains uncertain but the possibility of serious moral harm cannot be excluded, the precautionary principle has been proposed as a framework for ethical governance.</p><p><strong>Methods: </strong>This article critically examines the applicability of the precautionary principle to human brain organoid research through normative analysis. It clarifies core normative elements of precautionary principle and evaluates its relevance to emerging ethical challenges in brain organoid research.</p><p><strong>Results: </strong>The analysis identifies several major governance challenges, including the epistemic limitations of similarity-based inference, tensions between evidentiary standards and precautionary obligations, and the risks of ethics dumping. These problems reveal broader governance gaps rather than theoretical disagreements, underscoring the need for institutional adaptation in advance of definitive scientific evidence.</p><p><strong>Conclusions: </strong>The article argues that precautionary governance in human brain organoid research should avoid both excessive restriction and ethical complacency. It proposes strategies including dynamic and graded regulation, proportionality-based safeguards, and stronger international coordination. These approaches aim to balance ethical vigilance with responsible scientific innovation in a rapidly evolving field.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2717416"},"PeriodicalIF":4.4,"publicationDate":"2026-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148714293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Against the current: Sole authorship as method in contemplative and conceptual scholarship.","authors":"Heather Kempton","doi":"10.1080/08989621.2026.2714974","DOIUrl":"https://doi.org/10.1080/08989621.2026.2714974","url":null,"abstract":"<p><p>In the context of escalating authorship inflation and growing concern about research integrity, this article examines sole authorship as an epistemically and ethically grounded methodological condition within specific forms of contemplative and conceptual scholarship. Focusing on forms of inquiry in which interpretation constitutes the primary analytic process, I argue that sole authorship supports a continuous and traceable interpretive arc, central to epistemic integrity. In such contexts, continuity of interpretation not only enables conceptual coherence but also underpins ethical accountability by ensuring that responsibility for interpretive decisions remains clearly identifiable across the analytic process. Framed as a contemplative method grounded in mindful solitude, understood as an intentional orientation toward inward integration, sole authorship is situated within contemplative psychology and extended to methodologies such as Intuitive Inquiry, heuristic inquiry, hermeneutic phenomenology, and autoethnography, where interpretive validity depends on a sustained authorial perspective. While collaborative research remains essential across many domains, this article identifies conditions under which a unified authorial voice provides methodological advantages not fully reproduced through distributed authorship. The argument is therefore not that sole authorship offers a general solution, but that it functions as a context-specific stance aligned with the epistemic and ethical demands of contemplative scholarship.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2714974"},"PeriodicalIF":4.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148708461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distinguishing Contributor Listing from acknowledgments: Preserving the human dimension of scholarly recognition.","authors":"Yana Suchikova","doi":"10.1080/08989621.2026.2716269","DOIUrl":"https://doi.org/10.1080/08989621.2026.2716269","url":null,"abstract":"<p><p>Holcombe et al. (2026) propose practical mechanisms for making specific non-author research contributions more visible through ORCID identifiers, CRediT information, manuscript submission systems, and JATS-XML metadata. We support this aim but argue that its implementation requires a clearer distinction between two questions: how substantive contributions should be formally credited, and how broadly authors may acknowledge the human relationships and circumstances underlying scholarly work. We propose two complementary categories: a structured Contributor Listing for machine-readable author and non-author contributions and narrative Acknowledgments for gratitude and contextual recognition. This distinction would advance visibility and accountability without allowing the standardization of contributor credit to become the standardization of gratitude.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2716269"},"PeriodicalIF":4.4,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148698329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristen Intemann, Gitte Adler Reimer, Thomas Ingeman-Nielsen, Josephine Nymand, Ingelise Olesen, Elizabeth Rink, Aviâja Rosing Jakobsen, Christina Viskum Lytken Larsen
{"title":"Promoting equitable research: What Greenland teaches us about research ethics.","authors":"Kristen Intemann, Gitte Adler Reimer, Thomas Ingeman-Nielsen, Josephine Nymand, Ingelise Olesen, Elizabeth Rink, Aviâja Rosing Jakobsen, Christina Viskum Lytken Larsen","doi":"10.1080/08989621.2026.2713420","DOIUrl":"https://doi.org/10.1080/08989621.2026.2713420","url":null,"abstract":"<p><p>Kalaallit Nunaat (Greenland) is increasingly becoming a site for international research to examine global climate change, biodiversity, deposits of rare earth elements, and various existing health disparities. Yet, there is no comprehensive code of ethical guidelines for responsible and culturally centered research there. International researchers conducting research in Kalaallit Nunaat are bound by research ethics regulations governed their home countries and institutions, but these are varied and, perhaps most importantly, were established independently of Kalaallit (Greenlanders). Consequently, in many cases, research in Kalaallit Nunaat has failed to benefit or prioritize populations there and, in some cases, has caused unintended harms. Here we provide an overview of some of the problems that have resulted from research in Kalaallit Nunaat. These problems were identified from 27 listening sessions held across Kalaallit Nunaat with community members, municipality leaders, and researchers over a five-year period (2020-2025). The themes that arose reveal certain key limitations with applying Western research ethics policies to the Kalaallit Nunaat context. Specifically, such policies tend to neglect research equity, reflect an individualistic rights-based framework of ethics that is limiting, and presuppose that only humans deserve moral consideration.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2713420"},"PeriodicalIF":4.4,"publicationDate":"2026-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Closing the paper mines.","authors":"Adrian Barnett, Jennifer Byrne","doi":"10.1080/08989621.2026.2626740","DOIUrl":"10.1080/08989621.2026.2626740","url":null,"abstract":"<p><p>Scientific fakery is a centuries old problem. Twinned with the long history of hard-working scientists earning fame for genuine discoveries, runs a tawdry history of those who were willing fabricate results to falsely gain prestige. Fraud in the past relied on bespoke fakery, but today's fraudsters can exploit the online scientific world to quickly create realistic looking papers on an industrial scale. Fraudsters are using open data sets to create meaningless analyses and combining these results with text from large language models. There has been an explosion of these low value papers using openly available and highly regarded data sets, such as the US National Health and Nutrition Examination Survey (NHANES). The paper miners will likely exploit whatever open data resources they can find until data custodians put more stringent controls in place, or journals and publishers push back. Some scientific data may be too open, even though making research data openly available is a recommended policy for increasing research integrity. Journals and researchers need to be aware of this new threat to research integrity.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2626740"},"PeriodicalIF":4.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146120645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Artificial Intelligence (AI) guidance for authors, peer reviewers, and editors: A content analysis of journal policies.","authors":"Deborah H Charbonneau, Mei Zhang","doi":"10.1080/08989621.2026.2632083","DOIUrl":"10.1080/08989621.2026.2632083","url":null,"abstract":"<p><p>This study aims to examine how scholarly journals advise authors, peer reviewers, and journal editors about the acceptable use of artificial intelligence (AI) in the scholarly publishing process.<b>Methods:</b> Using a content analysis method, policies from 80 journals were collected in August 2024 from publicly available websites. Data from the journal policies related to AI authorship and allowable AI use by authors, peer reviewers, and editors were entered into a spreadsheet and analyzed using descriptive statistics.<b>Findings:</b> The results show that 62.5% (<i>n</i> = 50) of the journal policies mentioned AI. 96% of these journals did not permit AI to be listed as an author. 54% of journals allowed authors to use AI tools to improve language in their manuscript, whereas using AI to generate images was prohibited by 26% of journals. 64% of journals did not provide any AI-related guidance for peer reviewers/editors.<b>Conclusion:</b> This research advances the literature by detailing journal policies regarding AI authorship, the allowed use of AI for authors and peer reviewers, and disciplinary distinctions in AI treatment. The findings underscore the need for enhanced guidance directed at authors, peer reviewers, and editors regarding the ethical and appropriate application of AI tools.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2632083"},"PeriodicalIF":4.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146221013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Emerging ethical duties in AI-mediated research: A case of data sovereignty in applying cross-national regulation.","authors":"Ricardo Ayala, Pedro Hervé-Fernández","doi":"10.1080/08989621.2026.2623487","DOIUrl":"10.1080/08989621.2026.2623487","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) is reshaping research practices, yet its ethical implications remain under‑examined, particularly in cross‑national contexts.</p><p><strong>Objective: </strong>To explore how AI integration into environmental science complicates informed consent, privacy and data sovereignty, and to identify the ethical duties that follow for researchers.</p><p><strong>Case context: </strong>Drawing on a Chilean case study that adopts the European Union's General Data Protection Regulation (GDPR) as a normative framework, we focus on everyday AI‑mediated tools embedded in research infrastructures (e.g., transcription, cloud services, meeting assistants) and the tensions they introduce.</p><p><strong>Findings: </strong>AI intensifies -rather than replaces- ethical accountability, especially where legal protections are weak or infrastructures unequal. Algorithmic opacity constrains researcher autonomy and undermines data sovereignty.</p><p><strong>Conclusions: </strong>A governance approach grounded in data sovereignty and researcher autonomy is required to safeguard consent, privacy, and accountability in AI‑mediated research.</p><p><strong>Implications for policy and practice: </strong>We propose a revised model of ethical governance to support researchers working across fragmented regulations and opaque AI systems.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2623487"},"PeriodicalIF":4.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146094834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}