geography meets geometry in redistricting
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GEOGRAPHY MEETS GEOMETRY IN REDISTRICTING Moon Duchin Segregation - PowerPoint PPT Presentation

GEOGRAPHY MEETS GEOMETRY IN REDISTRICTING Moon Duchin Segregation and compactness Intertwining of theory (metrics), technology, and human outcomes - sometimes perversely Role of demonstration plans as benchmarks Method of


  1. GEOGRAPHY MEETS GEOMETRY IN REDISTRICTING Moon Duchin

  2. • Segregation and compactness • Intertwining of theory (metrics), technology, and human outcomes - sometimes perversely • Role of demonstration plans as benchmarks • “Method of ensembles”

  3. COMPACTNESS

  4. COMPACTNESS • For instance, Pennsylvania Supreme Court asked for reporting of Polsby-Popper, Schwartzberg, Reock, Convex Hull, Population Polygon

  5. COMPACTNESS • For instance, Pennsylvania Supreme Court asked for reporting of Polsby-Popper, Schwartzberg, Reock, Convex Hull, Population Polygon • New, insanely simpler idea: cut edges

  6. COMPACTNESS • For instance, Pennsylvania Supreme Court asked for reporting of Polsby-Popper, Schwartzberg, Reock, Convex Hull, Population Polygon • New, insanely simpler idea: cut edges

  7. SEGREGATION

  8. SEGREGATION • Existing measures of segregation are almost all non-spatial (!) – Dissimilarity, Gini, etc

  9. SEGREGATION • Existing measures of segregation are almost all non-spatial (!) – Dissimilarity, Gini, etc • Moran’s I is a sprinkle of linear algebra but works as a black box, has many undesirable properties

  10. SEGREGATION • Existing measures of segregation are almost all non-spatial (!) – Dissimilarity, Gini, etc • Moran’s I is a sprinkle of linear algebra but works as a black box, has many undesirable properties • Network assortativity is generally defined for binary attributes

  11. SEGREGATION • Existing measures of segregation are almost all non-spatial (!) – Dissimilarity, Gini, etc • Moran’s I is a sprinkle of linear algebra but works as a black box, has many undesirable properties • Network assortativity is generally defined for binary attributes • VRDI project spun off a variant for demographics - clustering propensity or capy scores (ask me for preprint)

  12. SEGREGATION • Existing measures of segregation are almost all non-spatial (!) – Dissimilarity, Gini, etc • Moran’s I is a sprinkle of linear algebra but works as a black box, has many undesirable properties • Network assortativity is generally defined for binary attributes • VRDI project spun off a variant for demographics - clustering propensity or capy scores (ask me for preprint) • Segregation in practice: Chicago project – districtr.org/chicago

  13. WHAT ARE ALTERNATIVE PLANS FOR?

  14. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation

  15. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation

  16. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation

  17. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation

  18. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation • Also seeds for random walks…

  19. WHAT ARE ALTERNATIVE PLANS FOR? • Demo plans are benchmarks and be enormously influential for public discourse and for litigation • Also seeds for random walks… • Markov chain Monte Carlo (MCMC) gives you ways to sample representatively from the universe of plans - does a plan behave as though chosen only from the stated rules?

  20. MGGG • The redistricting problem is aggressively interdisciplinary - must forge collaborations of geographers, political scientists, urban sociologists, legal and political theorists, litigators, mathematicians and computer scientists, developers, … mggg.org/jobs districtr.org

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