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| 多模态视角下博士研究生就业质量智能评价体系及实践进路 |
| Intelligent System and Practical Approach for Evaluating Employment Quality of Doctoral Graduates from the Multimodal Perspective |
| 投稿时间：2026-01-20 |
| DOI：10.19834/j.cnki.yjsjy2011.2026.03.15 |
| 中文关键词: 博士研究生;就业质量;多模态数据;智能评价;人才培养 |
| 英文关键词: doctoral graduates;employment quality;multimodal data;intelligent evaluation;talent cultivation |
| 基金项目:国家自然科学基金面上项目“基于数据挖掘的我国大学生高质量就业研究:评价体系、影响因素和实现路径”(71874205);中国政法大学科研创新年度规划(中央高校基本科研业务费专项资金资助)项目“新质生产力对地区就业韧性的影响效应及机制研究”(25KYGH001);中国政法大学钱端升杰出学者支持计划资助项目 |
| 作者 | 单位 | | 王霆 | 中国政法大学 商学院, 北京 100088 | | 林申琦 | 中国政法大学 商学院, 北京 100088 |
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| 中文摘要: |
| 在推进高水平科技自立自强与产业结构升级的背景下,博士研究生作为国家战略人才力量的重要组成部分,其就业质量直接关系到教育链、人才链与创新链的协同效能。本研究聚焦博士研究生就业区域失衡、职业错位与能力错配的三重困境,探讨运用多模态数据融合技术的价值意蕴和实施逻辑,构建涵盖就业求职、初次就业与职业发展的全周期就业质量智能评价体系。运用LDA主题模型、德尔菲法与层次分析法,系统提炼博士研究生就业质量评价指标,融合结构化数据、文本数据与行为数据,运用多模态大模型算法,实现动态价值引领、个体能力画像与政策治理协同等智能评价结果应用。本研究提出建设三级联动多模态数据仓、开发双维度智能诊断工具、实施分阶段精准施策等实践进路,推动博士研究生从“学术单通道”向“多元高质量”转型。 |
| 英文摘要: |
| Against the backdrop of advancing high-level technological self-reliance and industrial upgrading, doctoral graduates represent a vital component of the national strategic talent reserve. Their employment quality directly influences the synergistic performance of the education chain, talent chain, and innovation chain.This study addresses the critical triple challenges in doctoral employment: regional imbalance, occupational misalignment, and skills mismatch. It explores the value implication and implementation logic by applying multimodal data fusion technology to construct a full-cycle intelligent evaluation system encompassing job hunting, initial employment, and career development.By integrating the Latent Dirichlet Allocation (LDA) topic model, the Delphi method, and the Analytic Hierarchy Process (AHP), this study systematically extracts key evaluation indicators for doctoral employment quality. It synthesizes structured data, textual data, and behavioral data, and employs multimodal large model algorithms to generate applicable solutions from intelligent evaluation result such as dynamic value-based guidance, individual’s competency profiling, and coordinated policy governance.This study also proposes practical pathways including constructing a hierarchical three-tier collaborative multimodal data warehouse, developing a two-dimensional intelligent diagnostic tool, and implementing phased, targeted intervention strategies. These approaches are designed to drive the transition of doctoral graduates from a "singular academic track" to "diverse, high-quality career pathways". |
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