Background: The peer review process is the cornerstone of scientific publishing act-ing as quality assurance mechanism. The process faces the challenges of recruitment of reviewers and assessment of the quality of the peer review proscess and quality of manuscripts. Objectives: The aim of this study was to evaluate trends in reviewer performance scores (R-scores), manuscript quality (M-scores), and their association with reviewer recommendations and editorial decisions at the Annals of African Surgery over a 7-year period. Methods: This is a retrospective cross-sectional audit of all peer review reports sub-mitted to the Annals of African Surgery between January 2017 and December 2023. Summary reports were generated from the online manuscript management system with the following variables: manuscript ID, submission year, manuscript revision cycle, reviewer ID, reviewer invitation response, reviewer recommendation, reviewer R-score, manuscript score (M-score), days from review assignment to completion, manuscript first decision, and manuscript final decision. Results: There was a low manuscript review acceptance rate of 29.9%. R-scores were generally stable with descriptively lower scores in later years with the longest median in 2023. There were no significant changes in M-scores while reviewer turnaround time varied significantly across years. There was a slight agreement between reviewer recommendations and editorial decisions. Conclusion: While reviewer acceptance rates improved significantly after 2019, there was no corresponding improvement in R-scores or M-scores. Future efforts should prioritize not only increasing reviewer participation but also strengthening the qual-ity and consistency of reviewer feedback to more effectively support manuscript development.
Scholarly publishing is undergoing a significant structural transition: progressive del-egation of editorial judgement to algorithmic systems. While the debate has focused on authors’ use of generative artificial intelligence (AI), the undisclosed use of AI by editorial intermediaries – specifically in the copyediting and peer review triage stages – has received less attention. This Viewpoint presents that opaque editorial AI use risks ‘semantic drift,’ a condition in which algorithmic processing compromises the epistemic integrity of the scientific record. In response, the integrated transparency protocol is proposed, a risk-based disclosure framework that operationalizes mean-ingful human oversight to ensure editorial responsibility remains with humans.
Fabricated references, citations to nonexistent sources, appeared at a rate of 56.9 per 10 000 biomedical papers indexed in early 2026, a more than 12-fold increase since 2023. Manuscript volume is rising faster than editorial capacity, and conventional peer review does not routinely verify references. This viewpoint argues that automated reference verification, integrated into submission workflows, is a practical and proportionate response. The technical readiness of current tools, the evidence gaps and economic barriers to adoption, and the structured editorial response triggered by fabricated references are examined. The core principle is ‘artificial intelligence should handle the verifiable; humans should judge the evaluable’.
Academic conferences are important for sharing knowledge and collaboration; however, the organization often entails practices that incur a significant environmental footprint. As sustainability emerges as a global concern, academic events should implement responsible practices that reduce waste, emissions, and resource consumption.These guidelines were developed and implemented during the planning of the 18th European Association of Science Editors (EASE) Conference. The approach involved a systematic examination of decisions in relation to the UN Sustainable Development Goals, with a focus on accessibility, inclusivity, reduced carbon footprint, responsible consumption, and participant experience.The resulting guidelines propose practical and adaptable strategies applicable to academic events, and help organizers reduce environmental impact and support broader sustainability goals.
交差性分析は、単一の変数のみを考慮する段階を超えて、ジェンダーと人種、地理的位置とカーストなど、交差において生じる複合的な影響を検討するものである。「科学技術における交差性分析ガイドライン(GIST)」は、研究者、査読付き学術誌の編集者、資金配分機関が、関連する科学技術領域において交差性分析を体系的に統合することを支援するものである。本ガイドラインは、戦略的に研究の優先順位を設定したり研究課題を形成したりする段階から、データ収集、分析、解釈に至るまで、それぞれの研究プロセスにおける定量的交差性分析のためのロードマップとして機能する。また、著者や査読誌の編集者が本ガイドラインを遵守できるように、本稿ではチェックリストを提示する。さらに、私たちは査読誌の投稿規定に GIST チェックリストを追加することを推奨したい。最終的な目標は、適切な場面で交差性分析が含まれるように、研究のデフォルトを再設定することである。交差性分析はより良い科学をもたらす。すなわち、研究における精確性は、社会政策および環境政策の有効性を最大限に高め、ひいては世界的な公平性と環境の持続可能性の向上に資するのである。
