This document summarizes a presentation about the future of electoral redistricting. It discusses how open data, transparent criteria, public participation, and open-source software can improve redistricting. Key points include:
- Open data is needed for evaluating proposals, modifying plans, and auditing the process. Keeping data open requires coordination.
- Criteria should be based on social science, validated, and allow for reproducibility and robustness against small changes.
- Public participation exists on a continuum from information seeking to proposing alternatives. It can increase engagement, legitimacy and accountability.
- Independent institutions are important to support criteria, funding, transparency and public participation in the process.
- Open-source software can enable
1. A Future for Electoral Redistricting
Micah Altman
Director of Research
MIT Libraries
Prepared for
International Seminar on Electoral
Districting
National Electoral Institute
Mexico City, Mexico
May 2018
2. Disclaimers
These opinions are our own, they are not the opinions of our
institutions, of any of the project funders, nor (with the exception of
co-authored previously published work) my collaborators.
Secondary disclaimer:
“It’s tough to make predictions, especially about the future!”
-- Attributed to Woody Allen, Yogi Berra, Niels Bohr, Vint Cerf, Winston Churchill, Confucius, Disreali [sic], Freeman Dyson, Cecil
B. Demille, Albert Einstein, Enrico Fermi, Edgar R. Fiedler, Bob Fourer, Sam Goldwyn, Allan Lamport, Groucho Marx, Dan Quayle,
George Bernard Shaw, Casey Stengel, Will Rogers, M. Taub, Mark Twain, Kerr L. White, etc.
2
3. Collaborators, Co-conspirators, and Supporters
Michael P. McDonald, Eric Magar, Allejandro Trelles
We thank the Sloan Foundation for research support.
3
4. 4
This Talk
The Core
Public Participation
Supporting Institutions
Emerging Enablers
Free and Open Software
Transparent Data
Valid and Meaningful Criteria
6. Open Data
6
• Wide recognition of the need for data:
• Persistent
• Unrestricted
• Complete
• Timely
• Machine-actionable
• Data should be sufficient to:
• Evaluate the policy consequences of
government proposals
• Modify and create new proposals
• Audit the government’s proposal
process
[data.gov] [icpsr.umich.edu]
[datarefuge.org] [adrf.upenn.edu]
Keeping data open requires coordinated
effort across sectors and institutions.
7. Reproducible and Externally Valid Criteria
7
‘Neutral’ criteria are not enough
[Parker, 1990. Black Votes Count]
Choosing criteria without a complete
theory of representational quality
● Robustness
insensitive to small changes in
definition + small uncertainty in data
● Replicability
repeatable, auditable, open
● Validity
strong empirical relationship
between measure and observable
representational outcomes
8. 8
● Based on social
science of choice
● Enabled by crowd-
sourced solutions
● Strengthened by
algorithmic
generation of
solutions
Predicting ‘Bias’ and ‘Responsiveness’
● Uses deep foundation of estimation of the
seats-vote function
[Edgeworth 1898; Tufte 1973; Niemi & Deegan 1978]
● Refined with computationally-intensive social
science & statistics for counterfactual estimation
[Grofman & King 2007]
Measuring Revealed Intent
[Tufte 1973] [Altman-McDonald 2014]
• Same mathematical
foundation can
produce indices of
predicted
competitiveness,
efficiency-gaps,
majority-control,
etc.
9. Open Software for Scoring and Generating Plans
9
Open scoring
[rangevoting.org] [bdistricting.com]
[Planscore.org]
Score-Based Generation
[DistrictBuilder.org]
10. Open Software for Public Deliberation & Submission
10
• Identify and share
community boundaries
• Comment on, evaluate,
and modify proposals
• Publish and submit
alternatives
1
en cada una de dichas etapas y entre los distintos actores para obtener mejores resultados en u
marco de total transparencia.
Figura 4. Despliegue de la cartografía electoral del Estado de México a nivel seccional en e
District Builder
[See: DistrictBuilder districtbuilder.org ]
12. Public Participation is a Continuum
12
Topical
Interest
Information
Seeking
Debate &
Commentary
Propose
Alternatives
Consultative
Government
Get the data
Draw the lines
Citizen commissions
Watch the News
Score plans
17. Observations
17
’Neutral ‘ criteria and ‘optimal’ algorithms are insufficient
○ Neutral criteria have political consequences
-- and optimization is much easier than representation
○ We should adopt reliable, externally valid, robust social science criteria
-- that measure representation outcomes
○ We should strengthen institutions
that promote transparency, accountability, public participation and deliberations
Open Technology Can Help
○ Software can bridge the skills gap to enable participation
○ Open software and data can promote accountability, deliberation
○ Keeping data open requires coordinated effort across sectors and institutions.
Public Participation Matters
● The public can create legal, reasonable redistricting plans
● Individuals view communities differently than professional
● Publicly created plans are different than professionally created plans
19. References
19
● Altman M, McDonald M. Redistricting by Formula: An Ohio Reform Experiment. American Politics Research. 2018 Jan;46(1):103-31.
● Trelles A, Altman M, Magar E, McDonald MP. Datos abiertos, transparencia y redistritación en México. Política y gobierno. 2016
Dec;23(2):331-64.
● Altman, Micah, and Michael P McDonald (2014) “Paradoxes of Political Reform: Congressional Redistricting in Florida”, in Jigsaw
Politics in the Sunshine State, University Press of Florida..
● Altman, Micah, and Michael P McDonald. (2014) “Public Participation GIS : The Case of Redistricting.” Proceedings of the 47th Annual
Hawaii International Conference on System Sciences. Computer Society Press (IEEE).
● Micah Altman, Michael P McDonald (2013) “A Half-Century of Virginia Redistricting Battles: Shifting from Rural Malapportionment to
Voting Rights to Public Participation”. Richmond Law Review.
● Mac Donald K. Adventures in redistricting: A look at the California Redistricting Commission. Election Law Journal. 2012 Dec
1;11(4):472-89.
● Micah Altman, Michael P McDonald (2012) Redistricting Principles for the Twenty-First Century, 1-26. In Case-Western Law Review 62
(4).
● Micah Altman, Michael P. McDonald (2012) Technology for Public Participation in Redistricting. In Redistricting and Reapportionment
in the West, Lexington Press.
● Michael Altman, Michael P McDonald (2011) BARD: Better automated redistricting, 1-28. In Journal Of Statistical Software 42 (4).
● Micah Altman, M MCDONALD (2010) The Promise and Perils of Computers in Redistricting, 69–159. In Duke J Const Law Pub Policy
● Richard G. Niemi & John Deegan, Jr., A Theory of Political Redistricting, 72 AM. POL. SCI. REV. 1304 (1978).
● Edward R. Tufte, The Relationship Between Seats and Votes in Two-Party Systems, 67 AM. POL. SCI. REV. 540 (1973).
● Frances Y. Edgeworth, Miscellaneous Applications of the Calculus of Probabilities, 51 J. ROYAL STAT. SOC’Y, 534, 534 (1898).
● Bernard Grofman & Gary King, The Future of Partisan Symmetry as a Judicial Test for Partisan Gerrymandering after LULAC v. Perry, 6
ELECTION L.J. 2 (2007).