This map shows the geographic impact of David H. Kaye'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 David H. Kaye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David H. Kaye more than expected).
This network shows the impact of papers produced by David H. Kaye. 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 David H. Kaye. The network helps show where David H. Kaye may publish in the future.
Co-authorship network of co-authors of David H. Kaye
This figure shows the co-authorship network connecting the top 25 collaborators of David H. Kaye.
A scholar is included among the top collaborators of David H. Kaye 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 David H. Kaye. David H. Kaye 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.
Jackson, Graham, et al.. (2015). Communicating the Results of Forensic Science Examinations. SSRN Electronic Journal.6 indexed citations
2.
Kaye, David H.. (2012). Likelihoodism, Bayesianism, and a Pair of Shoes. SSRN Electronic Journal.5 indexed citations
3.
Kaye, David H. & David A. Freedman. (2011). Reference Guide on Statistics. SSRN Electronic Journal.12 indexed citations
4.
Risinger, D. Michael, Samuel R. Gross, Michael S. Pardo, et al.. (2010). Bayes Wars Redivivus - An Exchange. eYLS (Yale Law School).9 indexed citations
5.
Kaye, David H.. (2010). Gina's Genotypes. 108(1). 51–57.1 indexed citations
6.
Kaye, David H. & Joseph L. Gastwirth. (2008). The Disappearance that Wasn't? 'Random Variation' in the Number of Women Supreme Court Clerks. SSRN Electronic Journal.1 indexed citations
7.
Kaye, David H.. (2008). The Error of Equal Error Rates. SSRN Electronic Journal.1 indexed citations
8.
Kaye, David H.. (2008). Rounding Up the Usual Suspects: A Logical and Legal Analysis of DNA Trawling Cases. North Carolina law review. 87. 425.6 indexed citations
9.
Kaye, David H., et al.. (2007). Statistics in the Jury Box: How Juror Respond to Mitochondial DNA Probabilities. SSRN Electronic Journal.4 indexed citations
10.
Kaye, David H.. (2006). Revisiting 'Dreyfus': A More Complete Account of a Trial by Mathematics. Minnesota law review. 91(3). 825–835.1 indexed citations
11.
Kaye, David H. & Michael E. Smith. (2003). DNA Identification Databases: Legality, Legitimacy, and the Case for Population-Wide Coverage. SSRN Electronic Journal. 2003(3). 413–459.5 indexed citations
12.
Imwinkelried, Edward J. & David H. Kaye. (2001). DNA Typing: Emerging or Neglected Issues. SSRN Electronic Journal.1 indexed citations
13.
Kaye, David H.. (1988). Plemel as a Primer on Proving Paternity. SSRN Electronic Journal. 24. 867.2 indexed citations
14.
Kaye, David H.. (1988). What is Bayesianism? A Guide for the Perplexed. SSRN Electronic Journal. 28. 161.1 indexed citations
15.
Kaye, David H.. (1987). Apples and Oranges: Confidence Coefficients and the Burden of Persuasion. Cornell law review/The Cornell law quarterly. 73(1). 54–77.14 indexed citations
16.
Kaye, David H.. (1986). Ruminations on Jurimetrics: Hypergeometric Confusion in the Fourth Circuit. SSRN Electronic Journal.1 indexed citations
17.
Kaye, David H.. (1986). Hypothesis Testing in the Courtroom. SSRN Electronic Journal.2 indexed citations
Kaye, David H. & Ira Mark Ellman. (1979). Probabilities and Proof: Can HLA and Blood Group Testing Prove Paternity?. 54. 1131.13 indexed citations
20.
Ellman, Ira Mark & David H. Kaye. (1979). Probabilities and Proof: Can HLA and Blood Group Testing Prove Paternity?. SSRN Electronic Journal.9 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.