Judging Debacle in Pairs Figure Skating

Evidence of block voting by judges at the 2002 Winter Olympics in Salt Lake City led to the awarding of Gold Medals to both a Russian and a Canadian pair. It also prompted calls for a fairer judging system that could monitor and correct for judge bias.

An enterprising science reporter for the Toronto, Canada, Globe and Mail, Stephen Strauss, contacted Marilyn Looney ("Figure Skating Fairness", RMT 10:2, p. 500). The result was a feature article on page F6, Feb. 16, 2002, with the headline: "New scoring system would have iced the gold for the Canadians."

It continued:
"It's the eternal question when it comes to skating competitions: Can the bias of judges be detected and eliminated? Stephen Strauss finds that something called the Rasch measurement may do the trick."

Here are some Rasch-related excerpts:
"Looney reported that in a Rasch-adjusted universe second-place winner [in 1994] American Nancy Kerrigan should have beaten out Ukrainian Oksana Baiul for the gold medal."

"`The outcome could have been adjusted for judges' severity in real time after all the scores were in. We do it all the time in educational testing,' says Mary Lunz of Measurement Research Associates, a Chicago company that uses the Rasch approach in medical certifications."

"In answer to the question of what a Rasch-type analysis would have meant for the Salt Lake City Olympics, John Michael Linacre, a U.S. statistician who was Looney's consultant for the earlier work, has done a simple computation of the `prejudice pattern' at work in the judging. ... `You can see there is a block vote by four judges and it is also surprising to see that the Polish and the Ukrainian judges were more lenient on the Russians than their own skaters,' Linacre says. ... And what would a program that adjusted for human error -- either intended or accidental -- have produced in medal rankings? `Thought you would ask this. Yes, a Canadian victory,' says Linacre ... But maybe not, other statisticians say."

Perhaps the "other statisticians" are correct, but the Figure is a factor plot of bias patterns across the 9 judges, in which the Russian, Ukrainian, French and Polish judges share rating patterns, particularly contrasting to those of the Canadian and German judges. This plot, which Strauss saw, is the result of a preliminary analysis employing Facets, Winsteps and Systat. The major factor has a strength or eigenvalue of 3.8, the minor factor one of 1.7. In general, independent judging should not produce eigenvalues above about 1.4.

Judge bias patterns (preliminary results)

Since then, Marilyn Looney has been interviewed by reporters for newspapers, radio and TV. Other Rasch practitioners have also been contacted.

One reporter asked, "What can you conclude from these findings - that is, they don't `prove' collusion, right?" He's right. Statistical methods can't prove causality, but they can point out patterns and trends that merit close inspection, and can also indicate where and what remedial actions may be needed.

Further analysis, prompted by reporter questions, has revealed other bias patterns among the judges. The plot is thickening!

If you wish to do your own analysis, the complete set of judge ratings can be found at www.icecalc.com.

John M. Linacre

Judging Debacle in Pairs Figure Skating Linacre, J.M. … Rasch Measurement Transactions, 2002, 15:4 p. 839-840

Rasch Books and Publications
Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, 2nd Edn. George Engelhard, Jr. & Jue Wang	Applying the Rasch Model (Winsteps, Facets) 4th Ed., Bond, Yan, Heene	Advances in Rasch Analyses in the Human Sciences (Winsteps, Facets) 1st Ed., Boone, Staver	Advances in Applications of Rasch Measurement in Science Education, X. Liu & W. J. Boone	Rasch Analysis in the Human Sciences (Winsteps) Boone, Staver, Yale
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes	Statistical Analyses for Language Testers (Facets), Rita Green	Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments (Facets), George Engelhard, Jr. & Stefanie Wind	Aplicação do Modelo de Rasch (Português), de Bond, Trevor G., Fox, Christine M	Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind	Rasch Measurement: Applications, Khine	Winsteps Tutorials - free Facets Tutorials - free	Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre	Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan
Other Rasch-Related Resources: Rasch Measurement YouTube Channel
Rasch Measurement Transactions & Rasch Measurement research papers - free	An Introduction to the Rasch Model with Examples in R (eRm, etc.), Debelak, Strobl, Zeigenfuse	Rasch Measurement Theory Analysis in R, Wind, Hua	Applying the Rasch Model in Social Sciences Using R, Lamprianou	El modelo métrico de Rasch: Fundamentación, implementación e interpretación de la medida en ciencias sociales (Spanish Edition), Manuel González-Montesinos M.
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar	Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch	Rasch Models for Measurement, David Andrich	Constructing Measures, Mark Wilson	Best Test Design - free, Wright & Stone Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias	Diseño de Mejores Pruebas - free, Spanish Best Test Design	A Course in Rasch Measurement Theory, Andrich, Marais	Rasch Models in Health, Christensen, Kreiner, Mesba	Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen

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