David-Barrett Tamas, Dunbar Robin I M
Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, United Kingdom; Universidad del Desarrollo, Facultad de Gobierno, CICS, Av. Plaza 680, San Carlos de Apoquindo, Las Condes, Santiago de Chile 7610658, Chile; Kiel Institute for the World Economy, Kiellinie 66, D-24105 Kiel, Germany; Population Research Institute, Väestöliitto, Kalevankatu 16, Helsinki 00101, Finland.
Department of Experimental Psychology, University of Oxford, South Parks Road, Oxford OX1 3UD, United Kingdom; Department of Computer Science, Aalto University School of Science, P.O.Box 15500, Espoo 00076, Finland.
J Theor Biol. 2017 Mar 21;417:20-27. doi: 10.1016/j.jtbi.2017.01.015. Epub 2017 Jan 14.
Traditional human societies are organised around kinship, and use kinship networks to generate large scale community projects. This is made possible by a combination of linguistic kin recognition, a uniquely human trait, which is mediated by the reliability of kin as collaborators. When effective fertility falls, this results in two simultaneous effects on social networks: there are fewer kin that can be relied on, and the limiting effect of the local kin-clustering becomes stronger. To capture this phenomenon, we used a model of kinship lineages to build populations with a range of fertility levels combined with a behavioural synchrony model to measure the efficiency of collective action generated on kin networks within populations. Our findings suggest that, whenever effective cooperation depends on kinship, falling fertility creates a crisis when it results in too few kin to join the community project. We conclude that, when societies transition to small effective kin networks, due to falling fertility, increased relative distance to kin due to urbanisation or high mortality due to war or epidemics, they will be able to remain socially cohesive only if they replace disappearing kin networks with quasi-kin alternatives based on membership of guilds or clubs.
传统人类社会围绕亲属关系组织起来,并利用亲属关系网络开展大规模社区项目。这通过语言上的亲属识别得以实现,语言上的亲属识别是人类独有的特征,它由亲属作为合作者的可靠性介导。当有效生育率下降时,这会对社会网络产生两种同时出现的影响:可依赖的亲属减少,并且当地亲属聚集的限制作用变得更强。为了捕捉这一现象,我们使用了亲属谱系模型来构建具有一系列生育水平的人口,并结合行为同步模型来衡量人口内部亲属网络上产生的集体行动效率。我们的研究结果表明,只要有效的合作依赖于亲属关系,生育率下降导致参与社区项目的亲属过少时,就会引发危机。我们得出结论,当社会由于生育率下降、城市化导致与亲属的相对距离增加或战争或流行病导致的高死亡率而过渡到小型有效亲属网络时,只有用基于行会或俱乐部成员身份的准亲属替代方案取代正在消失的亲属网络,它们才能保持社会凝聚力。