Tamar Kushnir

5.4k citations
106 papers · 3.8k · 1 hit paper · h-index 29

Impact in

Papers in

Tamar Kushnir

102 papers receiving 3.4k citations

Tamar Kushnir's Hit Papers

A Theory of Causal Learning in Children: Causal Maps and Bayes Nets. 2004 · 815 citations
8150+7+14Years since publication250500750

Peers

Tamar Kushnir
Comparison fields: 5 of 164
  • Developmental and Educational Psychology 2.0k
  • General Decision Sciences 182
  • Cognitive Neuroscience 1.1k
  • Social Psychology 786
  • Cultural Studies 252
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Countries citing papers authored by Tamar Kushnir

Since Specialization
Citations

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

Fields of papers citing papers by Tamar Kushnir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tamar Kushnir. 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 Tamar Kushnir. The network helps show where Tamar Kushnir may publish in the future.

Co-authors

The 25 scholars most cited alongside Tamar Kushnir, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tamar Kushnir Line = papers co-authored together Tamar Kushnir links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Theory of Causal Learning in Children: Causal Maps and Bayes Nets.
Hit paper breakdown →
2004815
2 1998342
3 2010192
4 2013166
5 2005144
6 1986137
7 2007120
8 1982100
9 201392
10 201286
11 201466
12 201566
13 201364
14 201362
15 200659
16 201357
17 200750
18 201745
19 201641
20 201541

About Tamar Kushnir

Tamar Kushnir is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience, Social Psychology, Education and Sociology and Political Science, having authored 106 papers that have together received 3.8k indexed citations. Recurring topics across this work include Child and Animal Learning Development (64 papers), Psychology of Moral and Emotional Judgment (17 papers), Cultural Differences and Values (17 papers), Social and Intergroup Psychology (7 papers), Educational Strategies and Epistemologies (7 papers), Early Childhood Education and Development (6 papers), Autism Spectrum Disorder Research (6 papers) and Bayesian Modeling and Causal Inference (6 papers). The work is most often cited by research in Developmental and Educational Psychology (2.0k citations), General Decision Sciences (182 citations), Cognitive Neuroscience (1.1k citations), Social Psychology (786 citations) and Cultural Studies (252 citations). Tamar Kushnir has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Alison Gopnik, David M. Sobel, Laura Schulz, David Danks, Fei Xu, Clark Glymour, Henry M. Wellman, Nadia Chernyak, Y Itzchak and Kalanit Grill‐Spector. Their work appears in journals such as Developmental Psychology, Cognitive Science, Cognition, Developmental Science and Psychological Science.

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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