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必要与如何：基于历史资料的量化数据库构建与分析——以大学生学籍卡片资料为中心的讨论

  

  1. 作者1：梁晨，南京大学中华民国史研究中心；
    作者2：董浩，香港科技大学社会科学部
  • 出版日期:2015-03-24 发布日期:2015-03-24
  • 通讯作者: 梁晨，南京大学中华民国史研究中心 E-mail:liangchen@nju.edu.cn
  • 基金资助:
    本文是国家社会科学基金青年项目（10CZS023）和香港优配研究金项目（16400714）的成果之一。

Construction and Analysis of Big Historical MicroLevel Data：A Brief Discussion with Examples of Data Gathered from University Student Registration Cards

  1. Author 1：LIANG Chen，Center for the Republic of China History Research，Nanjing University；
    Author 2：DONG Hao，Division of Social Science，The Hong Kong University of Science and Technology
  • Online:2015-03-24 Published:2015-03-24
  • Contact: LIANG Chen，Center for the Republic of China History Research，Nanjing University E-mail:liangchen@nju.edu.cn
  • Supported by:
    The research was supported by the Youth Project of the National Social Science Fund (10CZS023) and Hong Kong Research Grants Council General Research Fund Project (16400714).

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摘要： 随着“大数据”时代的到来，依靠大规模系统历史资料构建量化数据库并进行定量分析成为一种新的、行之有效的研究方法。如何将这类历史资料进行合理有效的编码和数据库化，并通过实证分析更好地帮助我们了解社会经济发展的历史经验和对当下的启示，成为学界需要加强探索和讨论的关键技术课题。本文试图借助笔者多年来整理、分析近现代中国高校大学生学籍卡资料的经验，说明这种新方法论视角用于定量分析历史资料的重要价值与必要性，以及可能存在的诸多挑战和可供参考的应对办法。希望藉此引起社会科学与人文学科学者对这种研究方法的关注、讨论、尝试与合作。

关键词: 定量分析方法 , 学籍卡, 历史资料 , 量化数据库

Abstract: Along with boosting public and professional interests in “big data”，construction and analysis of largescale microlevel data from voluminous historical sources become available and promising.Big historical microlevel data facilitate interdisciplinary and longitudinal social scientific research，of which implications are far beyond historical but related to a better understanding of change and continuity in human behavior and society.While China has one of the world’s best and largest collections of historical documents surviving to date，practice in construction and analysis of historical microlevel data remain limited.We therefore share our experience from an ongoing research project that uses more than 150 000 individual student registration cards from two Chinese elite universities to study the evolution of social inequality in higher education between 1950 and 2000.We hope to stimulate broader academic interest，discussion，exploration，and collaboration in research using big historical microlevel data for the betterment of social sciences and humanities.

Key words:  micro-level data , quantitative methodology , historical , college student registration