Conformity cannot be identified based on population-level signatures.
Conformity cannot be identified based on population-level signatures.
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DOI：
10.1038/srep36068
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发表时间：
2016-10-31
影响因子：
4.6
通讯作者：
Tennie C
中科院分区：
文献类型：
--
作者：
Acerbi A;van Leeuwen EJ;Haun DB;Tennie C
从众传播被定义为不成比例地复制大多数人的可能性，被认为是文化多样性出现和稳定的潜在机制。然而，在学科内和跨学科的模糊性仍然是如何识别顺从传输经验。在大多数研究中，人口水平的结果已被视为证据一致性传播的基准：个体复制大多数的概率与比例多数大小之间的S形关系。使用基于个人的模型，我们表明，在生态上合理的条件下，这种S形关系也可以检测到没有配备个人与从众偏见。在个体从群体中的一个固定的样本子集中随机复制，或者他们对一个可能的变体有偏好的情况下，会产生与顺从者偏差类似的S形模式。我们的研究结果值得重新审视的研究基础上，他们的一致性传输的结论完全在S形曲线。更一般地说，我们的研究结果表明，人口水平的结果解释为顺从传输可能被解释为其他个人层面的战略，需要更多的实证支持，以证明存在的个人层面的顺从偏见在人类和其他动物。
Conformist transmission, defined as a disproportionate likelihood to copy the majority, is considered a potent mechanism underlying the emergence and stabilization of cultural diversity. However, ambiguity within and across disciplines remains as to how to identify conformist transmission empirically. In most studies, a population level outcome has been taken as the benchmark to evidence conformist transmission: a sigmoidal relation between individuals’ probability to copy the majority and the proportional majority size. Using an individual-based model, we show that, under ecologically plausible conditions, this sigmoidal relation can also be detected without equipping individuals with a conformist bias. Situations in which individuals copy randomly from a fixed subset of demonstrators in the population, or in which they have a preference for one of the possible variants, yield similar sigmoidal patterns as a conformist bias would. Our findings warrant a revisiting of studies that base their conformist transmission conclusions solely on the sigmoidal curve. More generally, our results indicate that population level outcomes interpreted as conformist transmission could potentially be explained by other individual-level strategies, and that more empirical support is needed to prove the existence of an individual-level conformist bias in human and other animals.
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DOI：
10.1098/rspb.2010.0705
发表时间：
2010-11-07
影响因子：
4.7
作者：
Franz, Mathias;Matthews, Luke J.
通讯作者：
Matthews, Luke J.
影响因子：
3.7
作者：
Claidière N;Bowler M;Brookes S;Brown R;Whiten A
通讯作者：
Whiten A
影响因子：
64.8
作者：
Aplin, Lucy M.;Farine, Damien R.;Morand-Ferron, Julie;Cockburn, Andrew;Thornton, Alex;Sheldon, Ben C.
通讯作者：
Sheldon, Ben C.
影响因子：
4.4
作者：
Coultas, JC
通讯作者：
Coultas, JC
影响因子：
2.5
作者：
Galef, Bennett G.;Whiskin, Elain E.
通讯作者：
Whiskin, Elain E.