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[1] G. Marston,et al. Unemployed citizen or ‘at risk’ client? Classification systems and employment services in Denmark and Australia , 2010 .
[2] J. Friedman. Special Invited Paper-Additive logistic regression: A statistical view of boosting , 2000 .
[3] Tapio Pahikkala,et al. Predicting Unemployment with Machine Learning Based on Registry Data , 2020, RCIS.
[4] C. Wendtland. Bundesagentur für Arbeit , 2012 .
[5] Sarah Bernhard,et al. Courses or individual counselling: does job search assistance work? , 2014 .
[6] Rachel K. E. Bellamy,et al. AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias , 2018, ArXiv.
[7] Kristina Lerman,et al. A Survey on Bias and Fairness in Machine Learning , 2019, ACM Comput. Surv..
[8] Nathan R. Kuncel,et al. Pushing the Limits for Judgmental Consistency: Comparing Random Weighting Schemes with Expert Judgments , 2020, Personnel Assessment and Decisions.
[9] Catherine McDonald,et al. Risk Technology in Australia: The Role of the Job Seeker Classification Instrument in Employment Services , 2003 .
[10] Alex Pentland,et al. Fair, Transparent, and Accountable Algorithmic Decision-making Processes , 2017, Philosophy & Technology.
[11] Ruben L. Bach,et al. Participating in a panel survey changes respondents’ labour market behaviour , 2019 .
[12] Irena Kogan. New Immigrants ― Old Disadvantage Patterns? Labour Market Integration of Recent Immigrants into Germany , 2011 .
[13] Astrid Mager,et al. Algorithmic Profiling of Job Seekers in Austria: How Austerity Politics Are Made Effective , 2020, Frontiers in Big Data.
[14] Alan Manning,et al. Gender Gaps in Unemployment Rates in OECD Countries , 2004, Journal of Labor Economics.
[15] Ludo Struyven,et al. Using Artificial Intelligence to classify Jobseekers: The Accuracy-Equity Trade-off , 2020, Journal of Social Policy.
[16] E. L. Kelly. Clinical versus statistical prediction: A theoretical analysis and review of the evidence. , 1955 .
[17] R. Ghani,et al. Validation of a Machine Learning Model to Predict Childhood Lead Poisoning , 2020, JAMA network open.
[18] P. O'Connell,et al. National Profiling of the Unemployed in Ireland , 2009 .
[19] Stefan Seth,et al. The Sample of Integrated Labour Market Biographies , 2010 .
[20] Alexandra Chouldechova,et al. A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions , 2018, FAT.
[21] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[22] Inigo Martinez de Rituerto de Troya,et al. Predicting , explaining , and understanding risk of long-term unemployment , 2018 .
[23] Toniann Pitassi,et al. Learning Fair Representations , 2013, ICML.
[24] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[25] P. O'Connell,et al. The Transition from Short- to Long-Term Unemployment: A Statistical Profiling Model for Ireland , 2012 .
[26] R. Ghani,et al. Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois. , 2017, American journal of public health.
[27] Stefan Seth,et al. European Data Watch: The German Integrated Employment Biographies Sample IEBS , 2007 .
[28] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[29] Bernd Fitzenberger,et al. Imputation Rules to Improve the Education Variable in the Iab Employment Subsample , 2005, Journal of Contextual Economics – Schmollers Jahrbuch.
[30] Ludo Struyven,et al. Statistical profiling in public employment services , 2019, OECD Social, Employment and Migration Working Papers.
[31] Jędrzej Niklas,et al. PROFILING THE UNEMPLOYED IN POLAND : SOCIAL AND POLITICAL IMPLICATIONS OF ALGORITHMIC DECISION MAKING , 2015 .
[32] George Athanasopoulos,et al. Forecasting: principles and practice , 2013 .
[33] Mohamad G. Alkadry,et al. A Systematic Review of the Gender Pay Gap and Factors That Predict It , 2017 .
[34] Frauke Kreuter,et al. Distributive Justice and Fairness Metrics in Automated Decision-making: How Much Overlap Is There? , 2021, ArXiv.
[35] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[36] Marita Jacob,et al. Marriage, Gender, and Class: The Effects of Partner Resources on Unemployment Exit in Germany , 2014 .
[37] R. Ghani,et al. Early Intervention Systems: Predicting Adverse Interactions Between Police and the Public , 2018 .
[38] D. Ruedin,et al. Ethnic discrimination in hiring decisions: a meta-analysis of correspondence tests 1990–2015 , 2016 .
[39] Christian Haas,et al. Fairness in Machine Learning: A Survey , 2020, ACM Comput. Surv..
[40] Martijn A. Wijnhoven,et al. The Work Profiler: A digital instrument for selection and diagnosis of the unemployed , 2014 .
[41] Andrew D. Selbst,et al. Big Data's Disparate Impact , 2016 .
[42] Devin G. Pope,et al. Implementing Anti-discrimination Policies in Statistical Profiling Models , 2011 .
[43] Artan Loxha,et al. Profiling the unemployed: a review of OECD experiences and implications for emerging economics , 2014 .