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.
Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms
19881.1k citationsAndrew H. Paterson, Eric S. Lander et al.Natureprofile →
Mendelian factors underlying quantitative traits in tomato: comparison across species, generations, and environments.
1991708 citationsAndrew H. Paterson, John D. Hewitt et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by John D. Hewitt
Since
Specialization
Citations
This map shows the geographic impact of John D. Hewitt'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 John D. Hewitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Hewitt more than expected).
This network shows the impact of papers produced by John D. Hewitt. 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 John D. Hewitt. The network helps show where John D. Hewitt may publish in the future.
Co-authorship network of co-authors of John D. Hewitt
This figure shows the co-authorship network connecting the top 25 collaborators of John D. Hewitt.
A scholar is included among the top collaborators of John D. Hewitt 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 John D. Hewitt. John D. Hewitt 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.
Hewitt, John D. & Robert M. Regoli. (2009). Valuing Textbook Writing in Academic Personnel Reviews. 37. 75–84.2 indexed citations
2.
Regoli, Robert M. & John D. Hewitt. (2007). Exploring criminal justice.4 indexed citations
3.
Hewitt, John D. & Robert M. Regoli. (2007). The Dilemma of Evaluating Faith-based Correctional Programs in Institutional and Community Settings. 35(2). 93–102.1 indexed citations
Regoli, Robert M., et al.. (2004). Location, Location, Location: The Transmission of Racist Ideology in Baseball Cards.. The Negro educational review. 55. 75–90.7 indexed citations
6.
Hewitt, John D., et al.. (2003). DIFFERENTIAL OPPRESSION THEORY AND FEMALE DELINQUENCY. 31(2). 165–174.1 indexed citations
Robinson, Nina L., John D. Hewitt, & A. B. Bennett. (1988). Sink Metabolism in Tomato Fruit. PLANT PHYSIOLOGY. 87(3). 727–730.102 indexed citations
14.
Paterson, Andrew H., et al.. (1988). Resolution of quantitative traits into Mendelian factors by using a complete linkage map of restriction fragment length polymorphisms. Nature. 335(6192). 721–726.1129 indexed citations breakdown →
Hewitt, John D.. (1985). Patterns of Female Criminality in Middletown: 1900 to 1920.. 38(2). 49–59.
17.
Hewitt, John D., Eric D. Poole, & Robert M. Regoli. (1985). Criminal justice in America, 1959-1984 : an annotated bibliography. Garland Pub. eBooks.1 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.