Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Rethinking individualism and collectivism: Evaluation of theoretical assumptions and meta-analyses.
20024.0k citationsDaphna Oyserman, Heather M. Coon et al.profile →
Does culture influence what and how we think? Effects of priming individualism and collectivism.
Countries citing papers authored by Daphna Oyserman
Since
Specialization
Citations
This map shows the geographic impact of Daphna Oyserman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daphna Oyserman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daphna Oyserman more than expected).
This network shows the impact of papers produced by Daphna Oyserman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daphna Oyserman. The network helps show where Daphna Oyserman may publish in the future.
Co-authorship network of co-authors of Daphna Oyserman
This figure shows the co-authorship network connecting the top 25 collaborators of Daphna Oyserman.
A scholar is included among the top collaborators of Daphna Oyserman based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Daphna Oyserman. Daphna Oyserman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Horowitz, Eric, Nicholas Sorensen, Nicholas Yoder, & Daphna Oyserman. (2018). Teachers Can Do It: Scalable Identity-Based Motivation Intervention in the Classroom.. Grantee Submission. 54. 12–28.20 indexed citations
6.
Sorensen, Nicholas, et al.. (2018). Developing and Testing a Scalable Identity-Based Motivation Intervention in the Classroom.. Society for Research on Educational Effectiveness.1 indexed citations
Oyserman, Daphna, Sheida Novin, George C. Smith, et al.. (2015). From Difficulty to Possibility: Interpretation of Experienced Difficulty, Motivation and Behavior. ACR North American Advances.1 indexed citations
Lee, Shawna J. & Daphna Oyserman. (2009). Expecting to work, fearing homelessness: The possible selves of low-income mothers. Deep Blue (University of Michigan).3 indexed citations
Oyserman, Daphna, Deborah Bybee, Carol T. Mowbray, & T. Hart-Johnson. (2005). When mothers have serious mental health problems: Parenting as a proximal mediator. Deep Blue (University of Michigan).1 indexed citations
15.
Oyserman, Daphna, Deborah Bybee, Carol T. Mowbray, & Sang Kyoung Kahng. (2004). Parenting self-construals of mothers with a serious mental illness: Efficacy, burden, and personal growth. Deep Blue (University of Michigan).1 indexed citations
Mowbray, Carol T. & Daphna Oyserman. (2003). Substance abuse in children of parents with mental illness: Risks, resiliency, and best prevention practices. Deep Blue (University of Michigan).1 indexed citations
18.
Oyserman, Daphna, Heather M. Coon, & Markus Kemmelmeier. (2002). Rethinking individualism and collectivism: Evaluation of theoretical assumptions and meta-analyses. Deep Blue (University of Michigan).3 indexed citations
Oyserman, Daphna. (1987). Possible Selves and Behavior: the Case of Juvenile Delinquency.. Deep Blue (University of Michigan).6 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.