Rachel Pulverman
- Developmental and Educational Psychology top 10%
- Experimental and Cognitive Psychology top 10%
- Language and Linguistics top 10%
- Cognitive Neuroscience
- Automotive Engineering
- Co-authors
- Roberta Michnick GolinkoffKathy Hirsh‐PasekLulu SongEtsuko HaryuPeter YellowleesMutsumi ImaiMandy J. MaguireSandra B. Vanegas
- Topics
- Child and Animal Learning Development (7 papers)Categorization, perception, and language (6 papers)Language Development and Disorders (3 papers)
- Cited by
- Developmental and Educational PsychologyExperimental and Cognitive PsychologyLanguage and Linguistics
- Journals
- Child DevelopmentDevelopmental PsychologyJournal of the American Academy of Child & Adolescent Psychiatry
- Partner nations
- United StatesChinaJapan
In The Last Decade
Rachel Pulverman
10 papers receiving 182 citations
Peers
Comparison fields: 5 of 33
- Developmental and Educational Psychology 131
- Experimental and Cognitive Psychology 99
- Language and Linguistics 32
- Cognitive Neuroscience 25
- Automotive Engineering 20
Countries citing papers authored by Rachel Pulverman
This map shows the geographic impact of Rachel Pulverman'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 Rachel Pulverman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachel Pulverman more than expected).
Fields of papers citing papers by Rachel Pulverman
This network shows the impact of papers produced by Rachel Pulverman. 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 Rachel Pulverman. The network helps show where Rachel Pulverman may publish in the future.
Co-authorship network of co-authors of Rachel Pulverman
This figure shows the co-authorship network connecting the top 25 collaborators of Rachel Pulverman. A scholar is included among the top collaborators of Rachel Pulverman 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 Rachel Pulverman. Rachel Pulverman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 3 | |
| 3 | 12 | |
| 4 | 27 | |
| 5 | 20 | |
| 6 | 55 | |
| 7 | 1 | |
| 8 | 49 | |
| 9 | Linguistic Input Directs Infants' Attention to Facilitate Word Learning | 1 |
| 10 | 15 |
About Rachel Pulverman
Rachel Pulverman is a scholar working on Developmental and Educational Psychology, Experimental and Cognitive Psychology and Applied Psychology, having authored 10 papers that have together received 189 indexed citations. Recurring topics across this work include Child and Animal Learning Development (7 papers), Categorization, perception, and language (6 papers) and Language Development and Disorders (3 papers). The work is most often cited by research in Developmental and Educational Psychology (131 citations), Experimental and Cognitive Psychology (99 citations) and Language and Linguistics (32 citations). Rachel Pulverman has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Roberta Michnick Golinkoff, Kathy Hirsh‐Pasek, Lulu Song, Etsuko Haryu, Peter Yellowlees, Mutsumi Imai, Mandy J. Maguire, Sandra B. Vanegas, Hiroyuki Okada and Shannon M. Pruden. Their work appears in journals such as Child Development, Developmental Psychology and Journal of the American Academy of Child & Adolescent Psychiatry.
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.