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Hamilton Court Judges, Research Paper Example
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Ratios of Reversal: A Probabilistic Analysis of U.S. appellate court decision
Introduction
Statistical analysis of judicial court decision provides the focus of query in the foregoing discussion. At present, probabilistic interpretation of legal fact finding is typically directed at evidentiary or quantified facts, but also to aggregate decision making outcomes as represented in this study. Risks attendant to interpretation of judicial procedure based upon mere belief do not serve to adequately represent the variance in logic models systems available to justices (Hillel, 2002). Model approaches to legal fact finding offer a range of methodologies toward precision in application of statutory rules. In the case of common law applications, judicial opinion is complicated by not only existing law, but the process oriented, previous court term decision toward resolution of later disputes. Contiguous decisions on cases adjudicated in appellate courts substantiate the best site for research in this area. ‘Next term’ case settlement by judges is quite explicit in common law countries like Australia, Canada, New Zealand, United Kingdom and United States (Moens, 2007). Cross breeding in global legal culture has also led to increased interest in ‘next term’ decision in civil law countries, as international law becomes more obtuse with legislative policies derived from precedent litigation, that is then often incorporated into national laws in those contexts.
As law becomes more enmeshed with changes to technologies and science in particular, the efficacy and prevalence of utilizing tools for decision might find advancement as justices now confront vast bodies of information and new knowledge formats, not to mention the implications of the number of lawsuits filed in response to everything from intellectual copyright on new innovations, to IT privacy invasion. The specialized expertise of Legal Analysts interested in term court decision may find reference in record (i.e. documentation) from the previous term, and are typically available for review in electronic form. Judicial opinion contains the elements, facts, policy issues and precedent laws informing the decision (Moens, 2007). The integration of economics and law is particularly promising in shared assessment of those records, as “algorithms for natural language processing and already traditional link-based ranking algorithms used by search engines stimulate research in this unexploited domain of legal documents” (Moens, 2007). Such studies are highly valuable, and the provenance of experts. The current study offers basic probabilistic analysis of enumerated judicial decision with the following results: 1) Probability of appeals by the courts; 2) Probability of Reversals by the courts; 3) Probability of appeal by Judge; 4) Probability of reversal by Judge; and 5) Probability of reversal given appeal by Judge. An Index of ranking by total cases for each Judge is also available for reference (Appendix).
Table 1
Court Probabilities | Diposed | Appeals | Reversals | Prob AP (%) | Prob AP (.) | |
Common | 43,945 | 1762 | 199 | 3.8 | 0.0383827 | |
Domestic | 30,499 | 106 | 17 | 0.3 | 0.0034615 | |
Muni | 108,464 | 500 | 104 | 0.5 | 0.0046058 |
Table 1: Probability of Appeals by Court
Table 2
Court Probabilities | Diposed | Appeals | Reversals | Prob RV (%) | Prob RV (.) | |
Common | 43,945 | 1762 | 199 | 0.4 | 0.0043349 | |
Domestic | 30,499 | 106 | 17 | 0.06 | 0.0005551 | |
Muni | 108,464 | 500 | 104 | 0.1 | 0.000958588 |
Table 2: Probability of Reversals by Court
Table 3
Judge | Disposed | Appealed | Reversed | Court | Prob AP (%) | Prob AP (.) |
Fred Cartolano | 3037 | 137 | 12 | Common | 4.3 | 0.0430006 |
Thomas Crush | 3372 | 119 | 10 | Common | 3.4 | 0.0339902 |
Patrick Dinkelacker | 1258 | 44 | 8 | Common | 3.3 | 0.0335877 |
Timothy Hogan | 1954 | 60 | 7 | Common | 3.0 | 0.0296882 |
Robert Kraft | 3138 | 127 | 7 | Common | 3.9 | 0.0388141 |
William Mathews | 2264 | 91 | 18 | Common | 3.8 | 0.038348 |
William Morrissey | 3032 | 121 | 22 | Common | 3.8 | 0.0381102 |
Norbert Nadel | 2959 | 131 | 20 | Common | 4.2 | 0.0421221 |
Arthur Ney Jr. | 3219 | 125 | 14 | Common | 3.8 | 0.0382496 |
Richard Niehaus | 3353 | 137 | 16 | Common | 3.9 | 0.0390758 |
Thomas Nurre | 3000 | 121 | 6 | Common | 3.9 | 0.0386952 |
John O’Connor | 2969 | 129 | 12 | Common | 4.1 | 0.041479 |
Robert Ruehlman | 3205 | 145 | 18 | Common | 4.3 | 0.430522 |
J. Howard Sundermann Jr. | 955 | 60 | 10 | Common | 5.9 | 0.0585365 |
Ann Marie Tracey | 3141 | 127 | 13 | Common | 3.9 | 0.00387077 |
Ralph Winkler | 3089 | 88 | 6 | Common | 2.8 | 0.0276468 |
Penelope Cunningham | 2729 | 7 | 1 | Domestic | 0.3 | 0.0025575 |
Patrick Dinkelacker | 6001 | 19 | 4 | Domestic | 0.03 | 0.003154 |
Deborah Gaines | 8799 | 48 | 9 | Domestic | 0.5 | 0.00542 |
Ronald Panioto | 12970 | 32 | 3 | Domestic | 0.2 | 0.0024605 |
Mike Allen | 6149 | 43 | 4 | Muni | 0.7 | 0.0069399 |
Nadine Allen | 7812 | 34 | 6 | Muni | 0.4 | 0.0043301 |
Timothy Black | 7954 | 41 | 6 | Muni | 0.5 | 0.0051243 |
David Davis | 7736 | 43 | 5 | Muni | 0.4 | 0.0363175 |
Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni | 0.6 | 0.0063789 |
Karla Grady | 5253 | 6 | 0 | Muni | 0.1 | 0.0011409 |
Deidra Hair | 2532 | 5 | 0 | Muni | 0.2 | 0.0019708 |
Dennis Helmick | 7900 | 29 | 5 | Muni | 0.4 | 0.0036551 |
Timothy Hogan | 2308 | 13 | 2 | Muni | 0.5 | 0.0051657 |
James Patrick Kenney | 2798 | 6 | 1 | Muni | 0.2 | 0.002139 |
Joseph Luebbers | 4698 | 25 | 8 | Muni | 0.5 | 0.0052842 |
William Mallory | 8277 | 38 | 9 | Muni | 0.5 | 0.0045552 |
Melba Marsh | 8219 | 34 | 7 | Muni | 0.4 | 0.0041162 |
Beth Mattingly | 2971 | 13 | 1 | Muni | 0.4 | 0.0043551 |
Albert Mestemaker | 4975 | 28 | 9 | Muni | 0.6 | 0.0055865 |
Mark Painter | 2239 | 7 | 3 | Muni | 0.3 | 0.0031124 |
Jack Rosen | 7790 | 41 | 13 | Muni | 0.5 | 0.0052631 |
Mark Schweikert | 5403 | 33 | 6 | Muni | 0.6 | 0.0060639 |
David Stockdale | 5371 | 22 | 4 | Muni | 0.4 | 0.0040763 |
John A. West | 2797 | 4 | 2 | Muni | 0.1 | 0.001427 |
Totals | 182908 | 2368 | 320 |
Table 3: Probability of Appeal by Judge
Case based reasoning (CBR) as it is known in the field of economics, looks to classificatory solutions to ‘next term’ decisions within legal analysis. Graph formats assist in illustration of the logic model. Others systems merely render a visual depiction that serves to assist the argument structure. The Araucaria system does not include in-depth fact pattern analysis of elements, but is intended to abstract those elements into a logical pattern or argument structure (Moens, 2007).
Figure 1
Figure: 1 Araucaria system
Table 4
Judge | Disposed | Appealed | Reversed | Court | Prob RV (%) | Prob RV (.) |
Fred Cartolano | 3037 | 137 | 12 | Common | 0.004 | 0.0037664 |
Thomas Crush | 3372 | 119 | 10 | Common | 0.3 | 0.0028563 |
Patrick Dinkelacker | 1258 | 44 | 8 | Common | 0.6 | 0.0061068 |
Timothy Hogan | 1954 | 60 | 7 | Common | 0.3 | 0.0034636 |
Robert Kraft | 3138 | 127 | 7 | Common | 0.2 | 0.0021393 |
William Mathews | 2264 | 91 | 18 | Common | 0.8 | 0.0075853 |
William Morrissey | 3032 | 121 | 22 | Common | 0.7 | 0.0069291 |
Norbert Nadel | 2959 | 131 | 20 | Common | 0.9 | 0.0093247 |
Arthur Ney Jr. | 3219 | 125 | 14 | Common | 0.4 | 0.0042839 |
Richard Niehaus | 3353 | 137 | 16 | Common | 0.5 | 0.0045636 |
Thomas Nurre | 3000 | 121 | 6 | Common | 0.2 | 0.0019187 |
John O’Connor | 2969 | 129 | 12 | Common | 0.4 | 0.0038585 |
Robert Ruehlman | 3205 | 145 | 18 | Common | 0.6 | 0.0057877 |
J. Howard Sundermann Jr. | 955 | 60 | 10 | Common | 1.0 | 0.009756 |
Ann Marie Tracey | 3141 | 127 | 13 | Common | 0.4 | 0.0039622 |
Ralph Winkler | 3089 | 88 | 6 | Common | 0.2 | 0.001885 |
Penelope Cunningham | 2729 | 7 | 1 | Domestic | 0.04 | 0.003653 |
Patrick Dinkelacker | 6001 | 19 | 4 | Domestic | 0.07 | 0.000664 |
Deborah Gaines | 8799 | 48 | 9 | Domestic | 0.1 | 0.0010162 |
Ronald Panioto | 12970 | 32 | 3 | Domestic | 0.02 | 0.0002306 |
Mike Allen | 6149 | 43 | 4 | Muni | 0.06 | 0.0006455 |
Nadine Allen | 7812 | 34 | 6 | Muni | 0.08 | 0.0007641 |
Timothy Black | 7954 | 41 | 6 | Muni | 0.07 | ,0007499 |
David Davis | 7736 | 43 | 5 | Muni | 0.06 | 0.00064223 |
Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni | 0.2 | 0.002439 |
Karla Grady | 5253 | 6 | 0 | Muni | 0 | 0 |
Deidra Hair | 2532 | 5 | 0 | Muni | 0 | 0 |
Dennis Helmick | 7900 | 29 | 5 | Muni | 0.06 | 0.0006301 |
Timothy Hogan | 2308 | 13 | 2 | Muni | 0.09 | 0.0008609 |
James Patrick Kenney | 2798 | 6 | 1 | Muni | 0.04 | 0.0003565 |
Joseph Luebbers | 4698 | 25 | 8 | Muni | 0.2 | 0.0016909 |
William Mallory | 8277 | 38 | 9 | Muni | 0.1 | 0.0010788 |
Melba Marsh | 8219 | 34 | 7 | Muni | 0.08 | 0.0008474 |
Beth Mattingly | 2971 | 13 | 1 | Muni | 0.03 | 0.000335 |
Albert Mestemaker | 4975 | 28 | 9 | Muni | 0.2 | 0.0017956 |
Mark Painter | 2239 | 7 | 3 | Muni | 0.1 | 0.0013339 |
Jack Rosen | 7790 | 41 | 13 | Muni | 0.2 | 0.0016573 |
Mark Schweikert | 5403 | 33 | 6 | Muni | 0.05 | 0.0005512 |
David Stockdale | 5371 | 22 | 4 | Muni | 0.07 | 0.0007411 |
John A. West | 2797 | 4 | 2 | Muni | 0.07 | 0.0007135 |
Totals | 182908 | 2368 | 320 |
Table 4: Probability of Reversal by Judge
Within the courtroom, a dense quality of rhetorical argument posits the case. Rhetorical Structure Theory offers much in terms of common law cases as fact elements become intertwined with the formation of law itself (Mann and Thompson (1988). This is particularly the case in business related contract litigation, where contract language constitutes the locus of the decision. As seen in Figure 2, exploitation of the RST tree structure with the representation of clauses and sentences in the nodes, discourse relations at the edges computation of individual nodes is based on their position in the tree hierarchy (Marcu 2002).
Figure 2
Figure 2: Rhetorical Structure
Table 5
Judge | Disposed | Appealed | Reversed | Court | Ratio AP:RV |
Fred Cartolano | 3037 | 137 | 12 | Common | 8.8 |
Thomas Crush | 3372 | 119 | 10 | Common | 8.4 |
Patrick Dinkelacker | 1258 | 44 | 8 | Common | 18.0 |
Timothy Hogan | 1954 | 60 | 7 | Common | 11.7 |
Robert Kraft | 3138 | 127 | 7 | Common | 5.5 |
William Mathews | 2264 | 91 | 18 | Common | 5.1 |
William Morrissey | 3032 | 121 | 22 | Common | 18.2 |
Norbert Nadel | 2959 | 131 | 20 | Common | 15.3 |
Arthur Ney Jr. | 3219 | 125 | 14 | Common | 11.2 |
Richard Niehaus | 3353 | 137 | 16 | Common | 11.7 |
Thomas Nurre | 3000 | 121 | 6 | Common | 5.0 |
John O’Connor | 2969 | 129 | 12 | Common | 9.3 |
Robert Ruehlman | 3205 | 145 | 18 | Common | 12.4 |
J. Howard Sundermann Jr. | 955 | 60 | 10 | Common | 5.0 |
Ann Marie Tracey | 3141 | 127 | 13 | Common | 10.2 |
Ralph Winkler | 3089 | 88 | 6 | Common | 6.8 |
Penelope Cunningham | 2729 | 7 | 1 | Domestic | 14.3 |
Patrick Dinkelacker | 6001 | 19 | 4 | Domestic | 21.0 |
Deborah Gaines | 8799 | 48 | 9 | Domestic | 18.8 |
Ronald Panioto | 12970 | 32 | 3 | Domestic | 9.9 |
Mike Allen | 6149 | 43 | 4 | Muni | 9.3 |
Nadine Allen | 7812 | 34 | 6 | Muni | 17.6 |
Timothy Black | 7954 | 41 | 6 | Muni | 14.6 |
David Davis | 7736 | 43 | 5 | Muni | 11.6 |
Leslie Isaiah Gaines | 5282 | 35 | 13 | Muni | 37.1 |
Karla Grady | 5253 | 6 | 0 | Muni | 0 |
Deidra Hair | 2532 | 5 | 0 | Muni | 0 |
Dennis Helmick | 7900 | 29 | 5 | Muni | 17.2 |
Timothy Hogan | 2308 | 13 | 2 | Muni | 15.4 |
James Patrick Kenney | 2798 | 6 | 1 | Muni | 16.7 |
Joseph Luebbers | 4698 | 25 | 8 | Muni | 32.0 |
William Mallory | 8277 | 38 | 9 | Muni | 23.7 |
Melba Marsh | 8219 | 34 | 7 | Muni | 20.6 |
Beth Mattingly | 2971 | 13 | 1 | Muni | 7.7 |
Albert Mestemaker | 4975 | 28 | 9 | Muni | 32.1 |
Mark Painter | 2239 | 7 | 3 | Muni | 42.9 |
Jack Rosen | 7790 | 41 | 13 | Muni | 31.7 |
Mark Schweikert | 5403 | 33 | 6 | Muni | 18.2 |
David Stockdale | 5371 | 22 | 4 | Muni | 18.2 |
John A. West | 2797 | 4 | 2 | Muni | 50.0 |
Totals | 182908 | 2368 | 320 |
Table 5: Reversal given appeal by Judge
Descriptive ratio of reversals above indicates probability of a reversal by each judge. Interestingly, while a range of statistical significance can be drawn from the results there is not enough information to draw solid conclusions. In spite of the scientific method of rule application within court decision, the factoring of human intuition, and especially in the common law courtroom with jury decision as an aspect of procedure, each case is in actuality a 50/50 chance for reversal.
Following the Moens (2007) innovation of the SALOMON system, and subsequent study toward summarization of Belgian criminal cases, user application of the instrument led to information on ‘next term’ decisions. The test set was comprised of 1000 cases. Of those cases, 882 were general complaints, and 112 specific — the latter mostly appellate court procedures. Recommendation to the findings resulted in the instrument illustrated in Figure 2.
Figure 3
Figure 3: SALOMON system
Conclusion
The initial query to the study included the proposition that analysis of judicial appellate court decision might result in outcomes that could be understood in terms of job performance. Due to the limits to information on the origin of the count as it pertains to number of decisions, and in regard to the specific nature of the cases represented by ‘disposals,’ ‘appeals’ and resultant ‘reversals,’ little might be said about those numbers short of immediate statistical significance as it relates to the actual dataset. In short, number of cases certainly supports the argument that a particular justice has spent more significant time in the courts than colleagues, but ultimately it does little to depict professional performance, nor rationale behind decision to the appeals without case record.
References
De Mot, J. and Depoorter, B. (2010). Tort Law and Probabilistic Litigation: How to Apply Multipliers to Address the Problem of Negative Value Suits. International Review of Law and Economics, 4 (3), 2010. doi:10.1016/j.irle.2010.04.003
Hillel, M.B. (2009). Probabilistic analysis in legal factfinding. Acta Psychologica, 56(1-3) August 1984, 267-284. doi:10.1016/0001-6918(84)90024-6
Mann, W.C. and Thompson, S.A. (1988). Rhetorical structure theory: Toward a functional theory of text organization. Text 8 (3) (1988), 243–281.
Marcu, D. (2000). The theory and practice of discourse parsing and summarization. Cambridge, MA: The MIT Press.
Moens, M.F. (2007). Summarizing court decisions. Information Processing & Management, 43 (6), November 2007, 1748-1764. doi:10.1016/j.ipm.2007.01.005
Saks, M.J and Schweitzer, N.J (2009). The Gatekeeper Effect: The Impact of Judges’ Admissibility Decisions on the Persuasiveness of Expert Testimony. Psychology, Public Policy, and Law, 15 ( 1), February 2009, 1-18.
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