基于大数据的文化心理分析

随着大数据技术与文化心理学的融合发展, 计算文化心理学作为一门新兴交叉学科逐渐兴起, 大尺度、近乎全样本的文化心理分析真正得以实现。计算文化心理学关注的文化变量主要围绕个人主义/集体主义这一文化心理学使用最为广泛的维度展开, 分析方法包括特征词典、机器学习、社会网络分析、仿真模拟等, 分析思路包括时间维度上的文化变迁效应以及空间维度上的文化地理效应。当然, 计算文化心理学在为传统文化心理研究提供新方法、新范式的同时, 也存在解码失真、样本偏差、词语多义性、隐私风险等局限, 未来研究应重视变量理论解释、文化动态演化分析、学科深度整合、生态效度等问题。     

空间、权力与知识:福柯的地理学转向

福柯是将空间议题置于社会理论架构之中的关键人物之一,本文评述福柯关于知识、权力与空间之间的互动关系的论述,从而展现福柯地理学转向的基本理论脉络。     

The Machines Take Over: A Comparison of Various Supervised Learning Approaches for Automated Scoring of Divergent Thinking Tasks

Traditionally, researchers employ human raters for scoring responses to creative thinking tasks. Apart from the associated costs this approach entails two potential risks. First, human raters can be subjective in their scoring behavior (inter-rater-variance). Second, individual raters are prone to inconsistent scoring patterns (intra-rater-variance). In light of these issues, we present an approach for automated scoring of Divergent Thinking (DT) Tasks. We implemented a pipeline aiming to generate accurate rating predictions for DT responses using text mining and machine learning methods. Based on two existing data sets from two different laboratories, we constructed several prediction models incorporating features representing meta information of the response or features engineered from the response’s word embeddings that were obtained using pre-trained GloVe and Word2Vec word vector spaces. Out of these features, word embeddings and features derived from them proved to be particularly effective. Overall, longer responses tended to achieve higher ratings as well as responses that were semantically distant from the stimulus object. In our comparison of three state-of-the-art machine learning algorithms, Random Forest and XGBoost tended to slightly outperform the Support Vector Regression.     

父母亲职压力与儿童对立违抗行为的关系:一项交叉滞后分析

采用亲职压力量表和对立违抗行为表现评估表调查了来自北京、山东和云南三地14所小学有ODD(oppositional defiant disorder)行为表现的301名儿童及其父母。通过为期两年的追踪研究,采用交叉滞后分析探讨了父母亲职压力与儿童的ODD行为之间的关系。结果发现:(1)在第一年和第二年的数据中,父母亲职压力和儿童的ODD行为表现均存在显著正相关;(2)第一年和第二年的父母亲职压力得分显著正相关,同样,两年的儿童ODD行为表现得分也显著正相关;(3)交叉滞后分析发现,对于有ODD行为表现的男孩来说,其父母第一年的亲职压力能预测他们第二年的ODD行为表现,但对于有ODD行为表现的女孩来说,其父母第一年的亲职压力并不能预测她们第二年的ODD行为表现;而不管是男孩,还是女孩,第一年的ODD行为表现都不能预测第二年的父母亲职压力。研究结果揭示出男孩父母的亲职压力可预测男孩的ODD行为表现,而不论是男孩或女孩的ODD行为表现都不能预测其父母亲职压力,说明父母亲职压力可能是男孩ODD行为表现的影响因素。     

认知冲突协调问题与心智的架构

心智架构或认知架构是指一个功能相对完整的认知系统的基本组织结构。经典认知科学的理论或模型大多采纳了某种类似于冯·诺依曼式计算机体系结构的心智架构,即认知系统由一些各司其职的心理模块与一个负责整合与协调的中枢部门所构成。进化心理学的众量模块性论题对经典认知科学的心智架构观提出了严厉挑战,并引发了许多争议。本文提出认知冲突协调问题是任何一个足够复杂的认知系统均需要处理的基本问题,并以此来审视关于心智架构的论战,指出此问题对众量模块性论题构成了严重的困难。     

Linking extreme response style to response processes: A cross‐cultural mixed methods approach

The aim of this study is to contribute to a better understanding of extreme response style in cross‐cultural research by integrating quantitative and qualitative evidence in a mixed methods design. In the quantitative phase, indexes of extreme response style, derived from quality of life measures from different international studies, were compared between Spain and the Netherlands. Results indicated that extreme responding was more common among Spanish than among Dutch in endorsement of items, but that the opposite was found for frequency scales including never as a response anchor. In the qualitative phase, cognitive interviews were conducted with 25 participants in each country. The integration of quantitative results and qualitative findings suggests that country differences in extreme response style may stem from various sources, including the more independent evaluation of each item by Dutch, the stronger connotations of never for Spanish and stronger emotions triggered by specific topics such as work satisfaction that was more strongly associated with insecurity for Spanish. It is concluded that the integration of quantitative and qualitative evidence can help to understand cross‐cultural similarities and differences in extreme response style.     

Raw Data Maximum Likelihood Estimation for Common Principal Component Models: A State Space Approach

The specifications of state space model for some principal component-related models are described, including the independent-group common principal component (CPC) model, the dependent-group CPC model, and principal component-based multivariate analysis of variance. Some derivations are provided to show the equivalence of the state space approach and the existing Wishart-likelihood approach. For each model, a numeric example is used to illustrate the state space approach. In addition, a simulation study is conducted to evaluate the standard error estimates under the normality and nonnormality conditions. In order to cope with the nonnormality conditions, the robust standard errors are also computed. Finally, other possible applications of the state space approach are discussed at the end.