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Social-material aspect of navigation technology: using structural topic models to identify the causes of ship accidents (1973–2018)
The Journal of Navigation ( IF 2.4 ) Pub Date : 2021-07-13 , DOI: 10.1017/s0373463321000576
Yang Chen 1 , Zhenghao Liu 1 , Han Zhou 2 , Jian Zheng 1 , Likun Wang 3
Affiliation  

What are the major factors contributing to ship accidents, and how do these factors evolve in the long term? This study addresses these two questions by leveraging an unsupervised machine learning method named structural topic modelling to identify the causes of ship accidents. The study analysed 2,341 task errors manually collected from 441 reports issued by four government agencies covering a 45-year time span. The results show that the structure of causes of ship accidents remained essentially the same during this period. This highlights the social-material aspect of navigation technology, indicating that the use of advanced technology may not necessarily lead to safer navigation practices, and the interaction between the technology and human agency must be focused on in the bridge management context. Additionally, the computer-assisted textual data analysis highlights pilot-related factors, which might be rooted in the unsupervised and difficult-to-verify handover procedures between pilots and captains, thereby underlining the importance of appropriate piloting regulations.



中文翻译:

导航技术的社会物质方面:使用结构主题模型来确定船舶事故的原因(1973-2018)

造成船舶事故的主要因素是什么,这些因素在长期内如何演变?本研究通过利用一种名为结构主题建模的无监督机器学习方法来确定船舶事故的原因,从而解决了这两个问题。该研究分析了从四个政府机构发布的涵盖 45 年时间跨度的 441 份报告中手动收集的 2,341 个任务错误。结果表明,这一时期船舶事故原因的结构基本保持不变。这突出了导航技术的社会物质方面,表明使用先进技术不一定会带来更安全的导航实践,技术与人类机构之间的互动必须在桥梁管理背景下关注。此外,

更新日期:2021-07-13
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