Access the full text.
Sign up today, get DeepDyve free for 14 days.
D. Schiek, L. Waddington, M. Bell (2007)
Cases, Materials and Text on National, Supranational and International Non-Discrimination Law
V. Schoder (2002)
Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non‐zero risk difference or non‐unity relative risk by C. P. Farrington and G. Manning, Statistics in Medicine 1990; 9:1447–1454Statistics in Medicine, 21
A. Stranieri, John Zeleznikow, Mark Gawler, B. Lewis (1999)
A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in AustraliaArtificial Intelligence and Law, 7
PA Riach, J Rich (2002)
Field experiments of discrimination in the market placeEcon J, 112
Australian Legislation. (a) Equal Opportunity Act – Victoria State, (b) Anti-Discrimination Act – Queensland State
P. Tan, M. Steinbach, Vipin Kumar (2005)
Introduction to Data Mining, (First Edition)
L. Sweeney (2002)
Achieving k-Anonymity Privacy Protection Using Generalization and SuppressionInt. J. Uncertain. Fuzziness Knowl. Based Syst., 10
P. Calem, Kevin Gillen, Susan Wachter (2003)
The Neighborhood Distribution of Subprime Mortgage LendingThe Journal of Real Estate Finance and Economics, 29
Federal Legislation. (a) Equal Credit Opportunity Act, (b) Fair Housing Act, (c) Intentional Employment Discrimination, (d) Equal Pay Act, (e) Pregnancy Discrimination Act
Vassilios Verykios, A. Elmagarmid, E. Bertino, Y. Saygin, Elena Dasseni (2004)
Association rule hidingIEEE Transactions on Knowledge and Data Engineering, 16
R. Agrawal, R. Srikant (1994)
Fast Algorithms for Mining Association Rules in Large Databases
D. Pedreschi, S. Ruggieri, F. Turini (2009)
Measuring Discrimination in Socially-Sensitive Decision Records
R. Klemm, D. Kaye, M. Aickin (1986)
Statistical Methods in Discrimination Litigation
Isabelle Chopin, Eirini-Maria Gounari (2010)
Developing anti-discrimination law in Europe : the 27 EU member states compared
G. Dymski (2006)
Discrimination in the Credit and Housing Markets: Findings and Challenges
H. Holzer, D. Neumark (2006)
Affirmative action: What do we know?Journal of Policy Analysis and Management, 25
D. Hand, W. Henley (1997)
Statistical Classification Methods in Consumer Credit Scoring: a ReviewJournal of the Royal Statistical Society: Series A (Statistics in Society), 160
F. Kamiran, T. Calders (2009)
Classification Without Discrimination
J. Rauch, M. Simunek (2005)
An Alternative Approach to Mining Association Rules
T. Makkonen (2007)
Measuring discrimination : data collection and EU equality law
Chen-Fu Chien, Li-Fei Chen (2008)
Data mining to improve personnel selection and enhance human capital: A case study in high-technology industryExpert Syst. Appl., 34
John Zeleznikow, George Vossos, D. Hunter (1993)
The IKBALS project: Multi-modal reasoning in legal knowledge based systemsArtificial Intelligence and Law, 2
G. Squires
Racial Profiling, Insurance Style: Insurance Redlining and the Uneven Development of Metropolitan Areas
R. Hunter (1992)
Indirect Discrimination in the Workplace
Conor Farrington, Godfrey Manning (1990)
Test statistics and sample size formulae for comparative binomial trials with null hypothesis of non-zero risk difference or non-unity relative risk.Statistics in medicine, 9 12
Ayça Hintoglu, Ali Inan, Y. Saygin, Mehmet Keskinöz (2005)
Suppressing data sets to prevent discovery of association rulesFifth IEEE International Conference on Data Mining (ICDM'05)
(2010)
Frequent itemset mining implementations repository. http://fimi.cs.helsinki.fi
(2005)
Affirmative action around the World: an empirical analysis
P. Riach, J. Rich (2002)
Field Experiments of Discrimination in the Market PlaceBehavioral & Experimental Economics
Liqiang Geng, Howard Hamilton (2006)
Interestingness measures for data mining: A surveyACM Comput. Surv., 38
Tim Harford (2008)
The Logic of Life
L Sterling, E Shapiro (1994)
The art of prolog, 2nd edn
European Union Legislation. (a) Racial Equality Directive, (b) Employment Equality Directive
H. Leung, L. Kupper (1981)
Comparisons of confidence intervals for attributable risk.Biometrics, 37 2
Gregory Squires (2003)
Racial Profiling, Insurance Style: Insurance Redlining and the Uneven Development of Metropolitan AreasJournal of Urban Affairs, 25
B. Johnston, Guido Governatori (2003)
Induction of defeasible logic theories in the legal domain
R. Lerner, Althea Nagai (2000)
Reverse discrimination by the numbersAcademic Questions, 13
A. Stranieri, John Zeleznikow (1999)
The evaluation of legal knowledge based systems
CT1, SBDA), P1 is SBDA/SBA, P1 >= MinP, pndrule(BD, C, CT2), confidence(CT2, CN1), P2 is CN1/CN, P2 >= MinP, P is min
Kwang-Ho Kim (2007)
Favoritism and reverse discriminationEuropean Economic Review, 51
L. Sterling, E. Shapiro (1994)
The art of Prolog (2nd ed.): advanced programming techniques
Gary Becker (1957)
The Economics of Discrimination
L. Thomas (2000)
A survey of credit and behavioural scoring: forecasting financial risk of lending to consumersInternational Journal of Forecasting, 16
Michael LaCour-Little (1998)
Discrimination in Mortgage Lending: A Critical Review of the LiteratureJournal of Real Estate Literature, 7
B. Kingsbury (1992)
Group rights and discrimination in international lawInternational Affairs, 68
Xiaoxin Yin, Jiawei Han (2003)
CPAR: Classification based on Predictive Association Rules
MJ Piette, PF White (1999)
Approaches for dealing with small sample sizes in employment discrimination litigationJ Forensic Econ, 12
E. Ziegel (1987)
Statistical Methods in Discrimination LitigationTechnometrics, 29
Christa Tobler (2008)
Limits and potential of the concept of indirect discrimination
Rainer Knopff (1986)
On Proving Discrimination: Statistical Methods and Unfolding Policy LogicsCanadian Public Policy-analyse De Politiques, 12
D. Pedreschi, S. Ruggieri, F. Turini (2008)
Discrimination-aware data mining
A. Agresti, M. Kateri (1991)
Categorical Data Analysis
Catherine Blake (1998)
UCI Repository of machine learning databases
GA Dymski (2006)
Handbook on the economics of discrimination
Jiawei Han, Hong Cheng, Dong Xin, Xifeng Yan (2007)
Frequent pattern mining: current status and future directionsData Mining and Knowledge Discovery, 15
H. Prakken, G. Sartor (2002)
The Role of Logic in Computational Models of Legal Argument: A Critical Survey
J. Wielemaker, T. Schrijvers, Markus Triska
Under Consideration for Publication in Theory and Practice of Logic Programming Swi-prolog
J. Gastwirth (1992)
Statistical Reasoning in the Legal SettingThe American Statistician, 46
(2007)
European handbook on equality data
(2005)
editor
K. Apt (1996)
From logic programming to Prolog
Ke Wang, B. Fung, Philip Yu (2005)
Template-based privacy preservation in classification problemsFifth IEEE International Conference on Data Mining (ICDM'05)
A. Agresti, B. Caffo (2000)
Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two FailuresThe American Statistician, 54
J. Gastwirth (1984)
Statistical Methods for Analyzing Claims of Employment DiscriminationIndustrial & Labor Relations Review, 38
O. Ashenfelter, R. Oaxaca (1987)
The Economics of Discrimination: Economists Enter the CourtroomThe American Economic Review, 77
EL) :- AC is
Chet Langin (2019)
Introduction to Data MiningScalable Comput. Pract. Exp., 9
Geoffrey Webb (2000)
Efficient search for association rules
Evelyn Ellis, Philippa Watson (2005)
EU Anti-Discrimination Law
F. Kamiran, T. Calders (2009)
Classifying without discriminating2009 2nd International Conference on Computer, Control and Communication
R. Newcombe (1998)
Interval estimation for the difference between independent proportions: comparison of eleven methods.Statistics in medicine, 17 8
John Yinger (1998)
Evidence on Discrimination in Consumer MarketsJournal of Economic Perspectives, 12
H. Holzer, D. Neumark (2004)
The economics of affirmative action
P. Kuhn (1990)
Sex Discrimination in Labor Markets: The Role of Statistical Evidence: ReplyThe American Economic Review, 80
M. Tian, Man-lai Tang, H. Ng, P. Chan (2008)
Confidence intervals for the risk ratio under inverse samplingStatistics in Medicine, 27
J. Fleiss (1973)
Statistical methods for rates and proportions
CT_BC, DELTA), confidence(CT_DBC, GAMMA), LB is 1/B2*(B2+GAMMA-1)/DELTA, merge
T. Sowell (2004)
Affirmative Action Around the World: An Empirical Study
Legislation. (a) Sex Discrimination Act, (b) Race Relation Act
B. Baesens, T. Gestel, Stijn Viaene, M. Stepanova, J. Suykens, J. Vanthienen (2003)
Benchmarking state-of-the-art classification algorithms for credit scoringJournal of the Operational Research Society, 54
(2005)
IUS Commune Casebooks for the Common Law of Europe Sowell T (ed) (2005) Affirmative action around the World: an empirical analysis
J. Reiczigel, Z. Abonyi-Tóth, Júlia Singer (2008)
An exact confidence set for two binomial proportions and exact unconditional confidence intervals for the difference and ratio of proportionsComput. Stat. Data Anal., 52
Michael Piette, Paul White (1999)
Approaches for Dealing with Small Sample Sizes in Employment Discrimination LitigationForensic Economics eJournal
(2007)
Proving discrimination cases -the role of situation testing. Centre For Equal Rights & Migration Policy Group, http://www.migpolgroup.com/publications
United Nations Legislation. (a) Convention on the Elimination of All forms of Racial Discrimination, (b) Convention on the Elimination of All forms of Discrimination Against Women
L. Sterling, E. Shapiro, Randy Garrett (1987)
The Art of PrologIEEE Expert, 2
We present a reference model for finding (prima facie) evidence of discrimination in datasets of historical decision records in socially sensitive tasks, including access to credit, mortgage, insurance, labor market and other benefits. We formalize the process of direct and indirect discrimination discovery in a rule-based framework, by modelling protected-by-law groups, such as minorities or disadvantaged segments, and contexts where discrimination occurs. Classification rules, extracted from the historical records, allow for unveiling contexts of unlawful discrimination, where the degree of burden over protected-by-law groups is evaluated by formalizing existing norms and regulations in terms of quantitative measures. The measures are defined as functions of the contingency table of a classification rule, and their statistical significance is assessed, relying on a large body of statistical inference methods for proportions. Key legal concepts and reasonings are then used to drive the analysis on the set of classification rules, with the aim of discovering patterns of discrimination, either direct or indirect. Analyses of affirmative action, favoritism and argumentation against discrimination allegations are also modelled in the proposed framework. Finally, we present an implementation, called LP2DD, of the overall reference model that integrates induction, through data mining classification rule extraction, and deduction, through a computational logic implementation of the analytical tools. The LP2DD system is put at work on the analysis of a dataset of credit decision records.
Artificial Intelligence and Law – Springer Journals
Published: Jun 5, 2010
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.