先锋队、落后者和孤立者:异常值和人口统计学研究

Liat Raz-Yurovich
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引用次数: 0

摘要

人口统计学是一个旨在分析人口变化的研究领域,它怎样才能从研究边远群体、国家或事件中受益?我们的分析工作表明,在人口转型中可能出现三种类型的异常值:1)先锋-转型的发起者;2)落后者——创新行为的后期采用者;3)孤立——那些从未加入转型的人。我们讨论了分析异常值的优势,阻碍此类研究的障碍,以及未能识别异常值的含义。确定先锋群体可能有助于人口统计学家定位人口转型的起点,做出更准确的预测,并更好地预测其他群体将经历的潜在轨迹。研究落后种群可以探索促进或阻碍采用新行为的机制。隔离可以帮助人口统计学家在受到其他变化影响之前了解人口过程的基本要素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vanguards, Laggards, and Isolates: Outliers and Demographic Research
In what way can demographic research, a field of study that aims to analyze population change, benefit from studying outlying groups, countries, or events? Our analytic work suggests that three types of outliers might emerge in demographic transitions: 1) Vanguards – the initiators of the transition; 2) Laggards – late adopters of the innovative behavior; and 3) Isolates – those who never joined the transition. We discuss the advantages of analyzing outliers, the barriers that impede such research, and the implications of failing to identify them. Identifying vanguard groups might help demographers locate the onset of a demographic transition, make more accurate projections, and better anticipate the potential trajectory that other groups will experience. Studying laggard populations allows exploring the mechanisms that facilitate or impede the adoption of a new behavior. Isolates can help demographers learn about the essentials of demographic processes, before they were affected by other changes.
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