Kubiszewski Ida, Zakariyya Nabeeh, Jarvis Diane
Crawford School of Public Policy, Australian National University, Canberra, Australia.
Research School of Economics, Australian National University, Canberra, Australia.
PeerJ. 2019 Feb 21;7:e6502. doi: 10.7717/peerj.6502. eCollection 2019.
Indicators that attempt to gauge wellbeing have been created and used at multiple spatial scales around the world. The most commonly used indicators are at the national level to enable international comparisons. When analyzing subjective life satisfaction (LS), an aspect of wellbeing, at multiple spatial scales in Australia, variables (drawn from environmental, social, and economic domains) that are significantly correlated to LS at smaller scales become less significant at larger sub-national scales. The reverse is seen for other variables, which become more significant at larger scales. Regression analysis over multiple scales on three groups (1) all individuals within the sample, (2) individuals with self-reported LS as dissatisfied (LS ≤ 5), and (3) individuals self-reporting LS as satisfied (LS > 5), show that variables critical for LS differ between subgroups of the sample as well as by spatial scale. Wellbeing measures need to be created at multiple scales appropriate to the purpose of the indicator. Concurrently, policies need to address the factors that are important to wellbeing at those respective scales, segments, and values of the population.
旨在衡量幸福的指标已在全球多个空间尺度上创建并使用。最常用的指标是国家层面的,以便进行国际比较。在澳大利亚多个空间尺度上分析主观生活满意度(LS)(幸福的一个方面)时,在较小尺度上与LS显著相关的变量(来自环境、社会和经济领域)在较大的次国家尺度上变得不那么显著。其他变量则相反,在较大尺度上变得更显著。对三组人群进行多尺度回归分析:(1)样本中的所有个体,(2)自我报告LS为不满意(LS≤5)的个体,以及(3)自我报告LS为满意(LS>5)的个体,结果表明,对LS至关重要的变量在样本子群体之间以及空间尺度上都有所不同。幸福衡量指标需要在适合指标目的的多个尺度上创建。同时,政策需要解决在这些各自的尺度、群体和人群价值观上对幸福至关重要的因素。