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了解你的社区:当地生态与个人经历预测北爱尔兰贝尔法斯特的社区认知

Knowing your neighbourhood: local ecology and personal experience predict neighbourhood perceptions in Belfast, Northern Ireland.

作者信息

Gilbert James, Uggla Caroline, Mace Ruth

机构信息

Department of Anthropology , University College London , 14 Taviton Street, London WC1H 0BW , UK.

Department of Anthropology, University College London, 14 Taviton Street, London WC1H 0BW, UK; Demography Unit, Department of Sociology, Stockholm University, 106 91 Stockholm, Sweden.

出版信息

R Soc Open Sci. 2016 Dec 7;3(12):160468. doi: 10.1098/rsos.160468. eCollection 2016 Dec.

Abstract

Evolutionary theory predicts that humans should adjust their life-history strategies in response to local ecological threats and opportunities in order to maximize their reproductive success. Cues representing threats to individuals' lives and health in modern, Western societies may come in the form of local ages at death, morbidity rate and crime rate in their local area, whereas the adult sex ratio represents a measure of the competition for reproductive partners. These characteristics are believed to have a strong influence over a wide range of behaviours, but whether they are accurately perceived has not been robustly tested. Here, we investigate whether perceptions of four neighbourhood characteristics are accurate across eight neighbourhoods in Belfast, Northern Ireland. We find that median age at death and morbidity rates are accurately perceived, whereas adult sex ratios and crime rates are not. We suggest that both neighbourhood characteristics and personal experiences contribute to the formation of perceptions. This should be considered by researchers looking for associations between area-level factors.

摘要

进化理论预测,人类应该根据当地的生态威胁和机遇来调整他们的生活史策略,以实现生殖成功率的最大化。在现代西方社会中,代表对个人生命和健康威胁的线索可能表现为当地的死亡年龄、发病率和犯罪率,而成人性别比则代表了对生殖伴侣的竞争程度。人们认为这些特征会对广泛的行为产生强烈影响,但它们是否被准确感知尚未得到充分验证。在这里,我们调查了北爱尔兰贝尔法斯特八个社区中,人们对四种社区特征的感知是否准确。我们发现,人们能够准确感知死亡年龄中位数和发病率,而成人性别比和犯罪率则不然。我们认为,社区特征和个人经历都有助于形成这些感知。寻找地区层面因素之间关联的研究人员应该考虑到这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40e7/5210677/a7ff41ecfbb4/rsos160468-g1.jpg

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