包括移民的性别维度至关重要,以避免在移民预测中的系统偏见
Athina Anastasiadou1,2, Emilio Zagheni1, Helga A G de Valk2
1Department of Digital and Computational Demography, Max Planck Institute for Demographic Research, Rostock 18057, Germany.
概括
移民研究面临挑战,原因是性别盲目的理论和有限的性别分类数据. 这项研究表明,这些问题降低了移民预测模型的准确性,特别是考虑到性别组成的模型.
科学领域:
- 社会学 社会学 社会学
- 人口统计学 人口统计学
- 性别研究是性别研究.
背景情况:
- 移民研究往往忽略了性别特异性的趋势.
- 现有的理论和数据缺乏性别包容性,影响分析.
- 移民研究中的性别盲导致不准确的预测.
研究的目的:
- 评估理论和方法限制对性别特定移民预测模型的影响.
- 评估理论中的性别盲目和数据稀缺如何影响移民预测.
- 为了比较不同模型在预测性别差异化移民流的准确性.
主要方法:
- 根据性别分类的移民流动分析.
- 确定性和概率性的重力类型模型的比较.
- 基于移民流的不同性别组成的模型性能评估.
主要成果:
- 基于移民流的性别组成的重力类型模型的预测性能中观察到的显著差异.
- 性别组成极大地影响了移民预测模型的准确性.
- 目前的预测方法受到理论和数据限制的破坏.
结论:
- 移民预测模型的准确性受到理论上的性别偏见和数据稀缺的严重阻碍.
- 迫切需要修订移民理论和方法,以纳入性别观点.
- 制定性别包容性框架对于更准确的移民预测至关重要.
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