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    大型煤炭企业应聘者安全意识智能评估方法研究

    Research on intelligent evaluation method of safety awareness of applicants in large coal enterprises

    • 摘要: 针对大型煤炭企业在招聘过程中存在的传统安全意识评估方法效率低、精度差等问题,探索了人工智能尤其是大语言模型的应用潜力,突破传统面试主观性与性格测试局限,提出基于人工智能分析开放式安全问卷的新方法。系统构建阶段,组织企业内的高安全绩效员工和普通安全绩效员工完成问卷调查,利用AI大模型分析其回答,构建人员安全行为倾向分类基准。应用阶段,应聘者完成同套问卷调查并经过AI大模型分析后,与基准比对进行安全行为倾向类型分类并生成安全意识评估报告。研究结果表明,该方法可提升评估效率,有效识别应聘者安全决策特质,为大型煤炭企业前端筛选高安全素养人才提供新思路与技术支撑。

       

      Abstract: Aiming at the problems of low efficiency and poor accuracy of traditional safety awareness assessment methods in the recruitment process of coal state-owned enterprises, this study explores the application potential of artificial intelligence, especially the large language model, breaks through the limitations of traditional interview subjectivity and personality test, and proposes a new method based on artificial intelligence to analyze open safety questionnaire. In the system construction stage, the high safety performance employees and ordinary safety performance employees in the organization enterprise complete the questionnaire survey, use the AI big model to analyze the answers, and construct the classification benchmark of personnel safety behavior tendency. In the application stage, after completing the same set of questionnaires and analyzing the AI model, the applicants classified the types of safety behavior tendencies and generated a safety awareness assessment report compared with the benchmark. The research results show that this method can improve the evaluation efficiency, effectively identify the safety decision-making characteristics of candidates, and provide new ideas and technical support for the front-end screening of high safety literacy talents in coal state-owned enterprises.

       

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