thai-chinese-gov-efficiency

Academic research agent for comparative analysis of governance structures in Thai and Chinese public business schools and their impact on educational efficiency. Use when: 1) Building theoretical frameworks for higher education governance 2) Designing mixed-methods research for cross-national institutional analysis 3) Managing longitudinal academic research workflows 4) Coordinating specialized sub-agents for literature review, data collection, and statistical analysis

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Install skill "thai-chinese-gov-efficiency" with this command: npx skills add 1829162846lw/thai-chinese-gov-efficiency

中泰高校治理效率研究代理

核心能力

1. 理论框架构建

  • 制度理论整合:结合新制度主义理论与资源依赖理论构建分析框架
  • 关键维度
    | 治理维度       | 中国指标                | 泰国指标               |
    |----------------|-------------------------|------------------------|
    | 行政集权度     | 教育部直接管理比例      | 大学自治委员会决策权重 |
    | 财政自主性     | 预算审批层级            | 校级财政自由裁量权     |
    | 人事控制度     | 编制审批制度            | 校长聘用自主权         |
    
  • 参考文件references/theoretical_framework.md(含制度变迁路径图)

2. 研究方法设计

  • 混合研究方法
    # 数据收集协议
    web_search --query "中国双一流高校治理白皮书 site:edu.cn" --count 5
    web_fetch https://public.moe.gov.cn/jytb_ghfz/ghfw/202312/t20231201_1093012.html
    exec python3 scripts/data_extractor.py --country=TH --source=mua
    
  • 质量控制
    • 三角验证:政策文本+院校年报+专家访谈
    • 信效度检验:Cronbach's α >0.7
  • 参考文件references/research_methods.md(含抽样方案模板)

3. 研究流程管理

graph LR
A[文献系统综述] --> B[指标体系构建]
B --> C[数据采集验证]
C --> D[DEA效率测算]
D --> E[回归分析]
E --> F[政策建议生成]
  • 里程碑管理
    {
      "Q3 2024": "完成5所中泰高校深度案例",
      "Q1 2025": "建立治理-效率面板数据库",
      "Q3 2025": "形成SSCI投稿初稿"
    }
    

4. 代理协调机制

  • 子代理调度
    spawn_subagent --skill literature-review --params "{\"keywords\": \"高校治理 中国 泰国\", \"years\": 2019-2024}""
    spawn_subagent --skill data-analysis --tool exec --command "Rscript scripts/efficiency_model.R"
    
  • 冲突解决:当数据矛盾时自动触发:
    exec python3 scripts/discrepancy_resolver.py --threshold=0.2
    

质量保障协议

  1. 每周执行 clawhub update --skill academic-research 同步最新方法论
  2. 所有数据源需通过 references/quality_checklist.md 验证
  3. 关键结论需经2名领域专家确认(记录在 assets/peer_review_log/

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