Jacquelyne J. Rivera
- Cognitive Neuroscience top 10%
- Developmental and Educational Psychology top 5%
- Developmental Biology top 5%
- Experimental and Cognitive Psychology
- Social Psychology
- Co-authors
- Anthony A. WrightRobert G. CookJulie J. NeiworthMelissa R. ShyanStephen F. SandsJuan D. DeliusStewart H. HulseJeffrey S. Katz
- Topics
- Child and Animal Learning Development (4 papers)Neuroscience and Music Perception (3 papers)Cognitive and developmental aspects of mathematical skills (3 papers)
- Journals
- Journal of Experimental Psychology GeneralJournal of Experimental Psychology Learning Memory and CognitionAnimal Cognition
- Partner nations
- United StatesGermany
In The Last Decade
Jacquelyne J. Rivera
8 papers receiving 422 citations
Peers
Comparison fields: 5 of 53
- Cognitive Neuroscience 228
- Developmental and Educational Psychology 192
- Developmental Biology 96
- Experimental and Cognitive Psychology 67
- Social Psychology 66
Countries citing papers authored by Jacquelyne J. Rivera
This map shows the geographic impact of Jacquelyne J. Rivera'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 Jacquelyne J. Rivera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jacquelyne J. Rivera more than expected).
Fields of papers citing papers by Jacquelyne J. Rivera
This network shows the impact of papers produced by Jacquelyne J. Rivera. 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 Jacquelyne J. Rivera. The network helps show where Jacquelyne J. Rivera may publish in the future.
Co-authorship network of co-authors of Jacquelyne J. Rivera
This figure shows the co-authorship network connecting the top 25 collaborators of Jacquelyne J. Rivera. A scholar is included among the top collaborators of Jacquelyne J. Rivera 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 Jacquelyne J. Rivera. Jacquelyne J. Rivera 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 | 58 | |
| 3 | 42 | |
| 4 | 118 | |
| 5 | 12 | |
| 6 | 11 | |
| 7 | 28 | |
| 8 | 177 |
About Jacquelyne J. Rivera
Jacquelyne J. Rivera is a scholar working on Statistics and Probability, Cognitive Neuroscience and Developmental and Educational Psychology, having authored 8 papers that have together received 452 indexed citations. Recurring topics across this work include Child and Animal Learning Development (4 papers), Neuroscience and Music Perception (3 papers) and Cognitive and developmental aspects of mathematical skills (3 papers). The work is most often cited by research in Developmental Biology (96 citations), Developmental and Educational Psychology (192 citations) and Cognitive Neuroscience (228 citations). Jacquelyne J. Rivera has collaborated with scholars based in United States and Germany. Frequent co-authors include Anthony A. Wright, Robert G. Cook, Julie J. Neiworth, Melissa R. Shyan, Stephen F. Sands, Juan D. Delius, Stewart H. Hulse, Jeffrey S. Katz, Jocelyne Bachevalier and Masako Jitsumori. Their work appears in journals such as Journal of Experimental Psychology General, Journal of Experimental Psychology Learning Memory and Cognition and Animal Cognition.
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.