Recruitment Threat Audit Index (RTAI): An Open-Source Intelligence Risk Scoring Model and Evidence Chain Audit Mechanism for Higher Education Talent Recruitment

This dataset is constructed based on the paper ‘Recruitment Threat Audit Index (RTAI): An Open-Source Intelligence Risk Scoring Model and Evidence Chain Audit Mechanism for Higher Education Talent Recruitment’. It aims to translate potential risks in university talent recruitment and academic qualification verification processes into a structured, computable scoring system in a reproducible and auditable manner. The dataset provides discrete scoring rules and weighting parameters for eight core indicators (I1–I8), alongside tiered thresholds (Green/Yellow/Orange/Red) and corresponding governance action recommendations. It is complemented by a ‘Claim–Evidence’ traceability table and links to external OSINT sources, ensuring end-to-end verifiability from conclusions to supporting evidence. This dataset facilitates risk identification, evidence chain auditing, and decision support for academic research and governance practices, while being scalable for broader institutional assessments and automated audit scenarios.

本数据集基于论文《招聘威胁审计指标（Recruitment Threat Audit Index，RTAI）：面向高校人才招聘的开源情报风险评分模型与证据链审计机制》构建。其目标是以可复现、可审计的方式，将高校人才招聘与学历资质核验流程中存在的潜在风险转化为结构化、可计算的评分体系。本数据集为8项核心指标（I1-I8）提供了离散化评分规则与权重参数，同时配套分级阈值（绿/黄/橙/红）及对应的治理行动建议。数据集还配套了“主张-证据”溯源表，并关联外部开源情报（Open-Source Intelligence，OSINT）数据源，确保从结论到佐证证据的全链路可验证性。本数据集可助力学术研究与治理实践中的风险识别、证据链审计与决策支持，同时具备可扩展性，可适配更广泛的机构评估与自动化审计场景。