Fantasy SCOTUS

FantasySCOTUS: Testing the Partisan Waters

The Tenth Justice Fantasy SCOTUS League.jpgEd. note: ATL has teamed up with the 10th Justice to predict how the Supreme Court may decide upcoming cases. CNN has called FantasySCOTUS the “hottest new fantasy-league game.”

Is the Supreme Court partisan? Although many perceive the Justices as mere political aids, do the numbers support this assertion? In this installment of 10th Justice, we will be exploring the perception that the Supreme Court Justices make their decisions based on partisan identity. For this purpose, we will be using a standardized majority ratio technique and confidence intervals to analyze Union Pacific Railroad, Salazar, Christian Legal Society, and McDonald.

Epidemiology, the study of factors affecting health and illness of populations, has yielded a standardized mortality ratio (SMR) which is used to make comparisons of mortality rates between different groups. In a slightly morbid twist on the Supreme Court, our FantasySCOTUS SMR is derived from the Epidemiology SMR.
The Epidemiology SMR is calculated by taking a proportion of observed number of deaths within the population of interest (i.e. 100 per 1,000) and dividing that by the expected number of deaths. The expected number of deaths is calculated by multiplying the population of interest by a proportion derived from a larger population (i.e. 10,000 per 100,000). A ratio that equal to 1 (as would be the case with the above numbers) implies that the population of interest is exactly like the larger population. A ratio greater than 1 implies a higher risk of death. A ratio less less than 1 implies lower risk of death. Additionally, SMR can be further refined using confidence intervals to determine if the deviation from 1 is statistically significant.
This SMR provides a method to test whether or not users perceive the Court as dominated by conservative ideology. Using the standardized mortality ratio, we can easily use the predictions to generate the observed number of times each Justice was in the majority. We will calculate the expected times each Justice voted in the majority by multiplying the total number of predictions by the percentage of affirm/reverse. To test the conservative majority, the higher percentage will be used to determine conservative Justices’ expectations, and the lower percentage for the liberal Justices.
Based on the information gained from other posts, Kennedy will be excluded from this process due to his tendency to be the deciding vote. His high majority count would greatly exceed any other Justice’s count. We calculate the confidence intervals with formula involving both the observed and expected values, which are obtained from our predictions.
From an interpretive standpoint, the assumptions concerning the affirm/reverse percentages are still applicable. Using the pure affirm/reverse percentages to determine expected values relies on the assumption that if a ratio is higher than 1 at a statistically significant level, then that particular Justice is less constrained by ideology, and is more likely to join in the majority beyond their ideological camp. However, if the ratio is less than 1 at a statistically significant level, then that Justice is more likely to vote in the minority, and support their own ideological camp.
So do people perceive SCOTUS as partisan? Results of the 10th Justice at

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