Using secondary data analyses to establish whether face-shape characteristics predict social judgments of faces consistently across world regions

我将结合对一个大型开放访问的人脸评级数据集和人脸图像数据库的分析（即，二次数据分析），以确定脸型特征是否能在世界各地一致地预测人脸的社会判断。大量研究表明，对面孔的社会判断（即我们根据他人的面部外貌形成的刻板印象）会影响重要的社会结果。例如，人们更喜欢与那些被认为特别有吸引力的人约会、交配、雇佣和投票。此外，看起来不值得信任的被告更有可能被判处死刑。因此，大量的跨学科文献研究了影响社会对面孔判断的因素。在这篇文献中，一个未解决的问题是脸型特征对面孔社会判断的影响在多大程度上在世界不同地区是一致的。关于这个问题的研究结果好坏参半（例如，Perrett et al., 1998 Nature; Scott et al., 2014 PNAS），他们用来评估面孔社会判断的方法最近受到了强烈批评。我最近领导了一份发表在《自然-人类行为》（Jones等人，2021年，b谷歌学者引用62次）上的注册报告，并评估了11个世界地区（非洲，亚洲，澳大利亚和新西兰，中美洲和墨西哥，东欧，中东，美国和加拿大，斯堪的纳维亚半岛，南美，英国，欧洲和欧洲）的11,000多名参与者对面孔的社会判断。和西欧)使用的方法专门解决了以前工作中使用的方法的局限性。利用主成分分析（PCA），本研究发现，面孔的社会判断是由可信度和支配性维度支撑的，并且这种结果模式在世界各地高度一致。然而，至关重要的是，Jones等人（2021）没有调查这些维度与脸型特征之间的关系。Jones等人（2021）报告的分析是对我领导的一个项目（与Lisa DeBruine和Jessica Flake一起）产生的数据集的分析，该项目是心理科学加速器（PSA; https://psysciacc.org）进行的第一个项目。PSA是一个由来自世界各地的研究人员组成的分布式网络，他们进行大规模的民主选择研究。Jones等人（2021）的数据集在PSA网络中被称为PSA001数据集（反映了它是PSA生成的第一个数据集），PSA001数据集和用于收集这些数据的面部刺激都是公开可用的。因此，我建议对这些数据进行预登记的二次分析，以评估脸型特征是否能在世界各地一致地预测面孔的社会判断。

I will combine analyses of a large open-access face-rating dataset and a face-image database (i.e., secondary data analyses) to establish whether face-shape characteristics predict social judgments of faces consistently across world regions.A large body of work has demonstrated that social judgments of faces (i.e., the stereotypic perceptions we form about other people based on their facial appearance) influence important social outcomes. For example, people prefer to date, mate with, hire, and vote for individuals perceived as being particularly attractive. Moreover, untrustworthy-looking court defendants are more likely to receive death sentences. Consequently, a large interdisciplinary literature has developed investigating the factors that shape social judgments of faces.An unresolved issue in this literature is the extent to which the effects of face-shape characteristics on social judgments of faces are consistent across different world regions. Findings from studies of this issue have been mixed (e.g., Perrett et al., 1998 Nature; Scott et al., 2014 PNAS) and the methods they used to assess social judgments of faces have recently been strongly criticised.I recently led a Registered Report that was published in Nature Human Behaviour (Jones et al., 2021, 62 citations in Google Scholar) and assessed over eleven thousand participants' social judgments of faces in eleven world regions (Africa, Asia, Australia and New Zealand, Central America and Mexico, Eastern Europe, The Middle East, United States and Canada, Scandinavia, South America, United Kingdom, and Western Europe) using methods that specifically addressed limitations of methods used in previous work. Using Principal Component Analyses (PCA), this study found that social judgments of faces were underpinned by trustworthiness and dominance dimensions and that this pattern of results was highly consistent across world regions. Crucially, however, Jones et al. (2021) did not investigate relationships between these dimensions and face-shape characteristics. The analyses reported in Jones et al. (2021) are analyses of a dataset produced by a project I led (with Lisa DeBruine and Jessica Flake) that was the first project to be conducted by the Psychological Science Accelerator (PSA; https://psysciacc.org). The PSA is a distributed network of researchers from across the world who conduct large-scale democratically selected studies. The dataset from Jones et al. (2021) is referred to within the PSA network as the PSA001 dataset (reflecting the fact it was the first dataset to be produced by the PSA) and both the PSA001 dataset and the face stimuli used to collect these data are publicly available. Consequently, I propose to carry out preregistered secondary analyses of these data to assess whether face-shape characteristics predict social judgments of faces consistently across world regions.