You have completed Module 3: Redistricting Data — What Changed with Callais. These four questions cover redistricting data types, the Gingles framework, and the post-Callais landscape.
Diagram 3.5 · Module 3 recap. Core redistricting data and the post-Callais shift from effects-based to intent-based analysis.
What does CVAP stand for, and why does it matter for redistricting analysis?
Correct! CVAP stands for Citizen Voting Age Population — citizens who are 18+ and eligible to vote. It comes from the ACS and is the standard denominator for evaluating majority-minority district claims under Section 2.Not quite. CVAP = Citizen Voting Age Population. It excludes non-citizens and minors. It comes from the ACS and is used to evaluate minority electoral opportunity under Section 2.
Which of the following best describes what Callais v. Landry (April 2026) changed about Section 2 VRA analysis?
Correct! Callais v. Landry raised the standard. States can no longer justify race-conscious district remedies solely on disparate impact — they must now demonstrate a strong basis in evidence of intentional discrimination.Not quite. Callais shifted from effects-based (disparate impact) to intent-based analysis. Gingles was not overruled, but the pathway to a remedy now requires showing intent.
What is an 'ensemble simulation' in redistricting analysis, and why does it matter after Callais?
Correct! Ensemble simulation generates thousands of maps satisfying neutral criteria and compares them to the enacted map. If the enacted map consistently produces fewer minority districts than the neutral ensemble, that deviation is circumstantial evidence of intent — precisely the kind of evidence needed after Callais.Not quite. Ensemble simulation compares the enacted map to thousands of neutral random maps. After Callais, this is valuable because it provides circumstantial evidence of intent when the enacted map systematically deviates from neutral outcomes.
The three Gingles factors require a plaintiff to show that a minority group is: (1) numerically sufficient and geographically compact; (2) politically cohesive; and (3) subject to white bloc voting that defeats its preferred candidates. Which data source is primarily used to demonstrate political cohesion (Factor 2)?
Correct! Political cohesion is demonstrated through RPV analysis — typically ecological inference applied to precinct-level election returns. Since individual ballots are secret, analysts infer group voting patterns from aggregate precinct data.Not quite. RPV analysis (ecological inference on precinct returns) is used to demonstrate cohesion. CVAP is used for Factor 1; RPV for Factors 2 and 3.