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| 高人口密度使个体向慢策略偏移 中文摘要 世界人口密度在过去60年间翻了2.5倍，然而，心理学界关于人口密度对心理影响的研究却一直在减少。研究没有使用传统的问卷法与实验方法，而是采用开放数据，从生命史理论的角度探讨人口密度对于个体生命史策略的影响。生命史理论认为个体需要对有限的资源进行权衡与分配，而人口密度的提高会增加一个社会中个体与个体之间的竞争激烈程度，从而进一步影响该社会中个体资源的可获取量与可支配量，导致个体适应性的调整生命史策略，研究假设高人口密度使个体向慢策略偏移；而高发展水平国家中由于资源相对充足，社会环境稳定，所以并不存在这一效应。基于世界银行与联合国人类发展报告的公开数据，通过国家水平上的数据分析发现，在低发展水平国家中，高人口密度降低了国家总和生育率，并且使国家的儿童入学率得到了提升，而在发展水平较高的国家中，则不存在该效应。研究所采用的数据均为开放数据，是在尝试社会心理学研究方法的另一种可能。研究结果为国家生育率的预测提供了新的思路，同时也有助于预测与规划未来的人口结构与人口水平，为政府及学界制定人口政策、社会福利制度、经济发展计划等提供了新的参考。 关键词：人口密度；人类发展指数；开放数据；生命史策略 II Abstract The population density of our world's has raised 2.5 times in the past 60 years,yet research on the psychological effects of population density has been declining. Instead of using conventional questionnaire and experimental methods,this study uses open data to examine the impact of population densityon individual life history strategies from the perspective of life history theory. The theory of life history holds that individuals need to balance and allocate limited resources,and the increase of population density will increase the intensity of competition among individuals in a society, which will further affect the availability and distribution of individual resources in the society, leading to the adaptive strategies of adjusting life history of individuals. Based on the open data of the World Bank and the United Nations Human Development Report, we found at the national level that high population density reduces the total fertility rate and increases the school enrollment rate of children in countries with low development level, while this effect does not exist in countries with high development level. The results of this study provide a new way of thinking for predicting the national fertility rate, and also help to predict and plan the population structure and population level in the future, and provide a reference for the government and academic circles to formulate population policies, social welfare systems and economic development plans. Key Words：population density; human development index; open data; life history strategy Abstract |
