|
| 从数据角度识别护理科技稿件中学术不端行为的方法与应对策略 |
| Strategies and coping methods for identifying academic misconduct articles in nursing technology journals from a data perspective |
| 投稿时间：2024-08-30 修订日期：2024-12-03 |
| DOI： |
| 中文关键词: 学术不端 护理科技期刊 数据 应对方法 |
| 英文关键词: academic misconduct nursing technology journal data response methods |
| 基金项目: |
|
| 摘要点击次数: 10 |
| 全文下载次数: 0 |
| 中文摘要: |
| 数据作为护理类科技期刊论文中的重要组成部分，反映了研究成果的真实性与准确性。针对护理类期刊论文特点，本文从数据的前后一致性、合理性、统计学方法的规律性探讨了识别学术不端稿件的方法，提出编辑和审稿专家应严谨假设、小心求证，从知、信、行角度强化数据审查行为，期刊方面也应加强对数据的规范化管理和作者的诚信教育。希望通过以上识别方法和应对策略，能够帮助护理类科技期刊编辑了解识别数据造假的稿件，充分发挥科技期刊防范学术不端中“守门员”的作用，杜绝学术不端稿件的刊出，助力健康学术生态圈的建设，营造良好的学术生态环境。 |
| 英文摘要: |
| Data, as an important component of nursing technology journal articles, reflects the authenticity and accuracy of research results. Based on the characteristics of submissions to nursing journals, this article explores methods for identifying academic misconduct from the perspectives of data consistency, rationality, and statistical regularity. It proposed that editors and reviewers should be rigorous in their assumptions and careful in their verification, and strengthen data review behavior from the perspectives of knowledge, belief, and practice. Journals should also strengthen standardized management of data and integrity education for authors. We hope that nursing science and technology journal editors can understand and identify data fraud articles through the above identification methods and response strategies, fully play the role of "gatekeepers" in preventing academic misconduct in science and technology journals, prevent the publication of academic misconduct articles, help build a healthy academic ecosystem, and create a good academic ecological environment. |
|
View Fulltext
查看/发表评论 下载PDF阅读器 |
| 关闭 |
