古怪时间地区的死亡风险:没有那么高

IF 2.2 2区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
J. Martín-Olalla
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引用次数: 1

摘要

最近,Gentry等人(2022)分析了2006年至2017年美国时区内东西梯度对车辆死亡人数的影响。他们区分了控制区域——那些在物理时区内与他们的冬季当地时间相对应的区域,称为太阳时间,例如德克萨斯州的休斯顿,以及测试区域——那些在物理时区以西的区域,称为偏心时间区域(ETL),例如德克萨斯州的阿马里洛。他们的结果总结在表3中,其中列出了太阳能组和ETL组的种群规模P、累积死亡率F和死亡率R = F/P。Gentry等人(2022)报告了东部、中部和山区ETL的较差评分(更高的死亡率):分别为23.8%、17.7%和26.5%,将太阳能位置与其相应的ETL进行了对比。在其他条件相同的情况下,东西梯度可能会影响交通事故率等社会问题。然而,Gentry等人(2022)报告的影响是惊人的大。我对他们的发现提供了另一种解释。在他们的分析中,作者隐含地假设F在不同的地理位置与P成比例。然而,当处理像F这样的异质社会量级时,应该考虑F}Pαe,其中αe是一个经验指数,它可能等于1,也可能不等于1。我提供了一个基于死亡率的类比。我得到了2000年以来西班牙按NUTS3地区分列的每周死亡人数(N = 52)。我将累积值的对数与每个地区平均人口的对数进行了测试。我发现αe = 0.921, 95%可信区间(CI)[0.864, 0.978]和Person 's
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fatality risks in eccentric time localities: Not that elevated
Dear Editors, Recently, Gentry et al. (2022) analyzed the impact of the east–west gradient within a US time zone on the vehicle fatalities from the year 2006 to the year 2017. They distinguished control localities—those inside the physical time zone corresponding to their winter local time, referred as solar, as an example Houston, Texas—and the tested localities—those outside, west of, their physical time zone, referred as Eccentric Time Locality (ETL), as an example Amarillo, Texas. Their results were summarized on their Table 3, where population sizes P, accumulated fatalities F, and the fatality rates R = F/P are listed for the solar and the ETL groups. Gentry et al. (2022) reported worse scores (larger fatalities) in the Eastern, Central, and Mountain ETL: 23.8%, 17.7%, 26.5%, respectively, comparing pairwise a solar location to their corresponding ETL. All else equal, east–west gradient may impact societal issues like traffic accident rates. However, the impact reported by Gentry et al. (2022) is staggering large. I offer an alternative explanation for their findings. In their analysis, the authors implicitly assume that F scales with P through different geographical localities. However, when dealing with heterogenous social magnitudes like F, one should consider F }Pαe, where αe is an empirical exponent, which may or may not be equal to one. I provide an analogy based on mortality. I got weekly numbers of deaths in Spain since the year 2000 disaggregated by NUTS3 regions (N = 52). I tested the logarithm of the accumulated values against the logarithm of the average population in every region. I found αe = 0.921 with 95% confidence interval (CI) [0.864, 0.978] and Person’s
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来源期刊
Time & Society
Time & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
3.90
自引率
10.00%
发文量
35
期刊介绍: Time & Society publishes articles, reviews, and scholarly comment discussing the workings of time and temporality across a range of disciplines, including anthropology, geography, history, psychology, and sociology. Work focuses on methodological and theoretical problems, including the use of time in organizational contexts. You"ll also find critiques of and proposals for time-related changes in the formation of public, social, economic, and organizational policies.
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