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Current Directions in Psychological Science最新文献

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“Asian” Is a Problematic Category in Research and Practice: Insights From the Bamboo Ceiling "亚裔 "在研究和实践中是一个有问题的类别：来自竹子天花板的启示
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-10-17 DOI: 10.1177/09637214241283406
Jackson G. Lu
{"title":"“Asian” Is a Problematic Category in Research and Practice: Insights From the Bamboo Ceiling","authors":"Jackson G. Lu","doi":"10.1177/09637214241283406","DOIUrl":"https://doi.org/10.1177/09637214241283406","url":null,"abstract":"This article spotlights a widespread problem in research and practice: Asians are commonly categorized as a monolithic group in the United States. Regarding research, my 24-year archival analysis of Psychological Science shows that most U.S. studies did not specify which Asian subgroup(s) were examined. Regarding practice, my analysis of the diversity, equity, and inclusion (DEI) webpages and latest diversity reports of S&P 100 companies finds that none of them differentiated between Asian subgroups. Such use of the generic category “Asian” is problematic because it masks important differences among Asian subgroups: (a) Of all ethnic groups in the United States, socioeconomic inequality among Asian subgroups is the highest and fastest growing; (b) U.S. studies show that East Asians (e.g., ethnic Chinese)—but not South Asians (e.g., ethnic Indians)—experience a “bamboo ceiling” in consequential contexts, including leadership attainment, academic performance in law and business schools, and starting salaries. Thus, lumping Asians together can obscure the challenges faced by certain Asian subgroups and jeopardize the attention and resources they need. More broadly, this article demonstrates the importance of differentiating between ethnic subgroups in research (e.g., theorization, surveys, and data analysis) and practice (e.g., diversity reports) to foster DEI.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"29 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142448429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Emerging Insights on the Role of Social Networks in Intergroup Friendship 关于社交网络在群体间友谊中的作用的新见解
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-10-12 DOI: 10.1177/09637214241283190
Kate M. Turetsky, J. Nicole Shelton
{"title":"Emerging Insights on the Role of Social Networks in Intergroup Friendship","authors":"Kate M. Turetsky, J. Nicole Shelton","doi":"10.1177/09637214241283190","DOIUrl":"https://doi.org/10.1177/09637214241283190","url":null,"abstract":"Research on intergroup friendships has historically focused on individuals and dyads. Only recently has research begun to examine intergroup friendship in the context of the broader web of social relationships in which individuals and dyads are embedded. This review highlights emerging research on the role of social networks in intergroup friendship, with a focus on interracial friendship. In particular, we examine how social networks shape opportunities to form intergroup friendships, influence intergroup attitudes, and affect ongoing intergroup interactions and relationships. This emerging work reveals how friendships across group lines are shaped not only by the individuals involved but also by their other friends, the attitudes of those around them, and the structure and context of their broader social network. Though nascent, social network research has already begun to offer novel insights into foundational intergroup theories and inform future interventions to foster intergroup friendships.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"1 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Effect Size Magnification: No Variable Is as Important as the One You’re Thinking About—While You’re Thinking About It 效应大小放大：任何变量都不如你正在思考的变量重要--在你思考的时候
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-10-12 DOI: 10.1177/09637214241268222
Linnea Gandhi, Benjamin S. Manning, Angela L. Duckworth
{"title":"Effect Size Magnification: No Variable Is as Important as the One You’re Thinking About—While You’re Thinking About It","authors":"Linnea Gandhi, Benjamin S. Manning, Angela L. Duckworth","doi":"10.1177/09637214241268222","DOIUrl":"https://doi.org/10.1177/09637214241268222","url":null,"abstract":"The goal of psychological science is to discover truths about human nature, and the typical form of empirical insights is a simple statement of the form x relates to y. We suggest that such “one-liners” imply much larger x- y relationships than those we typically study. Given the multitude of factors that compete and interact to influence any human outcome, small effect sizes should not surprise us. And yet they do—as evidenced by the persistent and systematic underpowering of research studies in psychological science. We suggest an explanation. Effect size magnification is the tendency to exaggerate the importance of the variable under investigation because of the momentary neglect of others. Although problematic, this attentional focus serves a purpose akin to that of the eye’s fovea. We see a particular x-y relationship with greater acuity when it is the center of our attention. Debiasing remedies are not straightforward, but we recommend (a) recalibrating expectations about the effect sizes we study, (b) proactively exploring moderators and boundary conditions, and (c) periodically toggling our focus from the x variable we happen to study to the non- x variables we do not.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"9 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning to Love Uncertainty 学会爱上不确定性
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-10-07 DOI: 10.1177/09637214241279539
Jessica L. Alquist, Roy F. Baumeister
{"title":"Learning to Love Uncertainty","authors":"Jessica L. Alquist, Roy F. Baumeister","doi":"10.1177/09637214241279539","DOIUrl":"https://doi.org/10.1177/09637214241279539","url":null,"abstract":"Uncertainty has a negative reputation. Not knowing what has happened or is going to happen is typically depicted as undesirable, and people often seek to minimize and avoid it. Research has shown that having a negative attitude toward uncertainty is associated with poor mental health and that certainty seeking can lead to accepting meager rewards and low-quality information. As a remedy for negative views of uncertainty, the present review discusses the functions of some typical responses to uncertainty as well as research on circumstances in which uncertainty can be leveraged to improve well-being. Uncertainty can focus attention, increase effort, and increase the intensity and duration of positive effect. Recognizing that there are situations in which uncertainty is desirable may be a first step toward improving attitudes toward uncertainty.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"10 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142384528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bayes in the Age of Intelligent Machines 智能机器时代的贝叶斯
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-09-21 DOI: 10.1177/09637214241262329
Thomas L. Griffiths, Jian-Qiao Zhu, Erin Grant, R. Thomas McCoy
{"title":"Bayes in the Age of Intelligent Machines","authors":"Thomas L. Griffiths, Jian-Qiao Zhu, Erin Grant, R. Thomas McCoy","doi":"10.1177/09637214241262329","DOIUrl":"https://doi.org/10.1177/09637214241262329","url":null,"abstract":"The success of methods based on artificial neural networks in creating intelligent machines seems like it might pose a challenge to explanations of human cognition in terms of Bayesian inference. We argue that this is not the case and that these systems in fact offer new opportunities for Bayesian modeling. Specifically, we argue that artificial neural networks and Bayesian models of cognition lie at different levels of analysis and are complementary modeling approaches, together offering a way to understand human cognition that spans these levels. We also argue that the same perspective can be applied to intelligent machines, in which a Bayesian approach may be uniquely valuable in understanding the behavior of large, opaque artificial neural networks that are trained on proprietary data.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"1 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142306213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Population-Level Administrative Data: A Resource to Advance Psychological Science 人口层面的管理数据：推动心理科学发展的资源
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-09-19 DOI: 10.1177/09637214241275570
Leah S. Richmond-Rakerd, Kallisse R. Dent, Signe Hald Andersen, Stephanie D’Souza, Barry J. Milne
{"title":"Population-Level Administrative Data: A Resource to Advance Psychological Science","authors":"Leah S. Richmond-Rakerd, Kallisse R. Dent, Signe Hald Andersen, Stephanie D’Souza, Barry J. Milne","doi":"10.1177/09637214241275570","DOIUrl":"https://doi.org/10.1177/09637214241275570","url":null,"abstract":"Population-level administrative data—data on individuals’ interactions with administrative systems, such as health-care, social-welfare, criminal-justice, and education systems—are a fruitful resource for research into behavior, development, and well-being. However, administrative data are underutilized in psychological science. Here, we review advantages of population-level administrative data for psychological research and provide examples of advances in psychological theory arising from administrative data studies. We focus on advantages in three areas: the collection and recording of population-level administrative data, the data’s large scale, and unique data linkages. We also describe ethical issues as well as methodological considerations and limitations in population administrative data research and outline future directions to enable psychological scientists to more fully capitalize on administrative data resources.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"11 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142245367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Traces of Our Past: The Social Representation of the Physical World 我们过去的痕迹物质世界的社会表征
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-09-14 DOI: 10.1177/09637214241268145
Julian Jara-Ettinger, Adena Schachner
{"title":"Traces of Our Past: The Social Representation of the Physical World","authors":"Julian Jara-Ettinger, Adena Schachner","doi":"10.1177/09637214241268145","DOIUrl":"https://doi.org/10.1177/09637214241268145","url":null,"abstract":"How do humans build and navigate their complex social world? Standard theoretical frameworks often attribute this success to a foundational capacity to analyze other people’s appearance and behavior to make inferences about their unobservable mental states. Here we argue that this picture is incomplete. Human behavior leaves traces in our physical environment that reveal our presence, our goals, and even our beliefs and knowledge. A new body of research shows that, from early in life, humans easily detect these traces—sometimes spontaneously—and readily extract social information from the physical world. From the features and placement of inanimate objects, people make inferences about past events and how people have shaped the physical world. This capacity develops early and helps explain how people have such a rich understanding of others: by drawing not only on how others act but also on the environments they have shaped. Overall, social cognition is crucial not only to our reasoning about people and actions but also to our everyday reasoning about the inanimate world.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"12 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
How Can Deep Neural Networks Inform Theory in Psychological Science? 深度神经网络如何为心理科学提供理论依据？
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-09-14 DOI: 10.1177/09637214241268098
Sam Whitman McGrath, Jacob Russin, Ellie Pavlick, Roman Feiman
{"title":"How Can Deep Neural Networks Inform Theory in Psychological Science?","authors":"Sam Whitman McGrath, Jacob Russin, Ellie Pavlick, Roman Feiman","doi":"10.1177/09637214241268098","DOIUrl":"https://doi.org/10.1177/09637214241268098","url":null,"abstract":"Over the last decade, deep neural networks (DNNs) have transformed the state of the art in artificial intelligence. In domains such as language production and reasoning, long considered uniquely human abilities, contemporary models have proven capable of strikingly human-like performance. However, in contrast to classical symbolic models, neural networks can be inscrutable even to their designers, making it unclear what significance, if any, they have for theories of human cognition. Two extreme reactions are common. Neural network enthusiasts argue that, because the inner workings of DNNs do not seem to resemble any of the traditional constructs of psychological or linguistic theory, their success renders these theories obsolete and motivates a radical paradigm shift. Neural network skeptics instead take this inability to interpret DNNs in psychological terms to mean that their success is irrelevant to psychological science. In this article, we review recent work that suggests that the internal mechanisms of DNNs can, in fact, be interpreted in the functional terms characteristic of psychological explanations. We argue that this undermines the shared assumption of both extremes and opens the door for DNNs to inform theories of cognition and its development.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"8 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142233298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Role of Real-World Statistical Regularities in Visual Perception 现实世界的统计规律在视觉感知中的作用
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-09-12 DOI: 10.1177/09637214241268083
Diane M. Beck, Evan G. Center, Zhenan Shao
{"title":"The Role of Real-World Statistical Regularities in Visual Perception","authors":"Diane M. Beck, Evan G. Center, Zhenan Shao","doi":"10.1177/09637214241268083","DOIUrl":"https://doi.org/10.1177/09637214241268083","url":null,"abstract":"Multiple models of vision propose that perception involves a process of prediction and verification. Here we argue that real-world statistical regularities—representations that, on average, more quickly make contact with meaning—serve as the basis of these predictions. We show that statistically regular images—those, we argue, that more closely match perceptual predictions—are more readily perceived and more efficiently processed than statistically irregular images.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"68 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using Cognitive Models to Improve the Wisdom of the Crowd 利用认知模型提高群众智慧
IF 7.2 1区 心理学
Current Directions in Psychological Science Pub Date : 2024-08-27 DOI: 10.1177/09637214241264292
Michael D. Lee
{"title":"Using Cognitive Models to Improve the Wisdom of the Crowd","authors":"Michael D. Lee","doi":"10.1177/09637214241264292","DOIUrl":"https://doi.org/10.1177/09637214241264292","url":null,"abstract":"The wisdom of the crowd is the finding that aggregating the judgments of many people can lead to surprisingly accurate group judgments. Usually statistical methods are used to aggregate people’s judgments, but there are advantages to using cognitive models instead. Crowd judgments based on cognitive modeling can (a) identify experts and amplify their judgments, (b) provide a representational structure for aggregating complicated multidimensional judgments, (c) debias judgments that are affected by heuristic cognitive processes or competitive social situations, and (d) diversify the crowd by incorporating predictions about judgments that have not been observed. Demonstrations of these advantages are provided in case studies involving ranking, probability estimation, and categorization problems.","PeriodicalId":10802,"journal":{"name":"Current Directions in Psychological Science","volume":"49 1","pages":""},"PeriodicalIF":7.2,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142084735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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