Nancy S. Kim

947 total citations
30 papers, 596 citations indexed

About

Nancy S. Kim is a scholar working on Developmental and Educational Psychology, Philosophy and Clinical Psychology. According to data from OpenAlex, Nancy S. Kim has authored 30 papers receiving a total of 596 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Developmental and Educational Psychology, 9 papers in Philosophy and 8 papers in Clinical Psychology. Recurrent topics in Nancy S. Kim's work include Child and Animal Learning Development (13 papers), Mental Health and Psychiatry (9 papers) and Psychotherapy Techniques and Applications (5 papers). Nancy S. Kim is often cited by papers focused on Child and Animal Learning Development (13 papers), Mental Health and Psychiatry (9 papers) and Psychotherapy Techniques and Applications (5 papers). Nancy S. Kim collaborates with scholars based in United States, Netherlands and Mexico. Nancy S. Kim's co-authors include Woo‐kyoung Ahn, Charles A. Sanislow, Benjamin M. Rottman, Jennelle E. Yopchick, Frank C. Keil, Laura R. Novick, Stefanie T. LoSavio, Daniel J. Paulus, Jeffrey S. Gonzalez and Joshua Knobe and has published in prestigious journals such as American Journal of Psychiatry, Journal of Experimental Psychology General and Journal of Experimental Psychology Learning Memory and Cognition.

In The Last Decade

Nancy S. Kim

30 papers receiving 567 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nancy S. Kim United States 13 206 169 141 122 114 30 596
Paolo Migone Italy 8 249 1.2× 93 0.6× 81 0.6× 49 0.4× 80 0.7× 64 517
Karl H. Wiedl Germany 16 183 0.9× 41 0.2× 216 1.5× 367 3.0× 120 1.1× 47 702
Antonio Godoy Spain 12 245 1.2× 17 0.1× 144 1.0× 46 0.4× 92 0.8× 54 449
Michael S. Brady United Kingdom 12 51 0.2× 230 1.4× 78 0.6× 40 0.3× 316 2.8× 35 571
Matthew Haigh United Kingdom 9 126 0.6× 14 0.1× 75 0.5× 45 0.4× 72 0.6× 29 334
Jennelle E. Yopchick United States 5 90 0.4× 14 0.1× 90 0.6× 34 0.3× 79 0.7× 7 304
James C. Mancuso United States 10 205 1.0× 77 0.5× 69 0.5× 53 0.4× 39 0.3× 28 492
F. Kräupl Taylor United Kingdom 11 189 0.9× 123 0.7× 100 0.7× 38 0.3× 100 0.9× 52 545
Julius Wishner United States 10 107 0.5× 49 0.3× 82 0.6× 77 0.6× 93 0.8× 25 405
John Lambie United Kingdom 8 127 0.6× 38 0.2× 143 1.0× 31 0.3× 219 1.9× 11 535

Countries citing papers authored by Nancy S. Kim

Since Specialization
Citations

This map shows the geographic impact of Nancy S. Kim'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 Nancy S. Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nancy S. Kim more than expected).

Fields of papers citing papers by Nancy S. Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nancy S. Kim. 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 Nancy S. Kim. The network helps show where Nancy S. Kim may publish in the future.

Co-authorship network of co-authors of Nancy S. Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Nancy S. Kim. A scholar is included among the top collaborators of Nancy S. Kim 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 Nancy S. Kim. Nancy S. Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kim, Nancy S., et al.. (2018). Systematic distortions in clinicians’ memories for client cases: Increasing causal coherence.. Journal of Experimental Psychology Learning Memory and Cognition. 45(2). 196–212. 2 indexed citations
2.
Ahn, Woo‐kyoung, Nancy S. Kim, & Matthew S. Lebowitz. (2017). The Role of Causal Knowledge in Reasoning About Mental Disorders. Oxford University Press eBooks. 12 indexed citations
3.
Kim, Nancy S., et al.. (2017). The effect of abstract versus concrete framing on judgments of biological and psychological bases of behavior. Cognitive Research Principles and Implications. 2(1). 17–17. 6 indexed citations
4.
Kim, Nancy S., et al.. (2015). Understanding Lay Assessments of Alcohol Use Disorder: Need for Treatment and Associated Stigma. Alcohol and Alcoholism. 51(1). 98–105. 12 indexed citations
5.
Kim, Nancy S., et al.. (2015). The influence of framing on clinicians’ judgments of the biological basis of behaviors.. Journal of Experimental Psychology Applied. 22(1). 39–47. 12 indexed citations
6.
Kim, Nancy S., et al.. (2013). Visual Causal Models Enhance Clinical Explanations of Treatments for Generalized Anxiety Disorder. Journal of Health Communication. 18(sup1). 103–117. 10 indexed citations
7.
Kim, Nancy S., Daniel J. Paulus, Thao Phuong Nguyen, & Jeffrey S. Gonzalez. (2012). Do Clinical Psychologists Extend the Bereavement Exclusion for Major Depression to Other Stressful Life Events?. Medical Decision Making. 32(6). 820–830. 8 indexed citations
8.
Kim, Nancy S., et al.. (2011). A proximity effect in adults’ contamination intuitions. Judgment and Decision Making. 6(3). 222–229. 21 indexed citations
9.
Yopchick, Jennelle E. & Nancy S. Kim. (2011). Causal Explanations Guide Inferences about Children’s Bizarre Behaviors. Cognitive Science. 33(33). 1 indexed citations
10.
Yopchick, Jennelle E. & Nancy S. Kim. (2011). Hindsight bias and causal reasoning: a minimalist approach. Cognitive Processing. 13(1). 63–72. 16 indexed citations
11.
Kim, Nancy S., et al.. (2011). How do practising clinicians and students apply newly learned causal information about mental disorders?. Journal of Evaluation in Clinical Practice. 19(1). 112–117. 4 indexed citations
12.
Rottman, Benjamin M., Nancy S. Kim, Woo‐kyoung Ahn, & Charles A. Sanislow. (2010). Can Personality Disorder Experts RecognizeDSM-IVPersonality Disorders From Five-Factor Model Descriptions of Patient Cases?. The Journal of Clinical Psychiatry. 72(5). 630–639. 15 indexed citations
13.
Kim, Nancy S. & Stefanie T. LoSavio. (2009). Causal explanations affect judgments of the need for psychological treatment. Judgment and Decision Making. 4(1). 82–91. 16 indexed citations
14.
Kim, Nancy S., et al.. (2009). ConceptBuilder: An open-source software tool for measuring, depicting, and quantifying causal models. Behavior Research Methods. 41(1). 128–136. 5 indexed citations
15.
Rottman, Benjamin M., Woo‐kyoung Ahn, Charles A. Sanislow, & Nancy S. Kim. (2009). Can Clinicians Recognize DSM-IV Personality Disorders From Five-Factor Model Descriptions of Patient Cases?. American Journal of Psychiatry. 166(4). 427–433. 83 indexed citations
16.
Kim, Nancy S., et al.. (2009). The conceptual centrality of causal cycles. Memory & Cognition. 37(6). 744–758. 8 indexed citations
17.
Kim, Nancy S., et al.. (2006). Causal Cycles in Categorization. eScholarship (California Digital Library). 28(28). 3 indexed citations
18.
Kim, Nancy S.. (2005). Stability and Instability Over Time in Explanatory Theories of Concepts. eScholarship (California Digital Library). 27(27). 1 indexed citations
19.
Kim, Nancy S. & Frank C. Keil. (2003). From symptoms to causes: Diversity effects in diagnostic reasoning. Memory & Cognition. 31(1). 155–165. 41 indexed citations
20.
Ahn, Woo‐kyoung, Laura R. Novick, & Nancy S. Kim. (2003). Understanding behavior makes it more normal. Psychonomic Bulletin & Review. 10(3). 746–752. 37 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.

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