Problem: The Chaldean community reported they were not aware of potential redistricting impacts to their community, learning of proposed boundary changes just three weeks before the final map deadline.
Possible Solution: To target outreach for potential communities of interest or “protected classes” (Voting Rights Act, Section 2 includes Race, Color, and Membership in a Language-minority group) and increase the potential for reaching these communities of interest, consider utilizing American Community Survey (ACS) data in advance of the decennial census data.
Problem: Commissioners received over 4,000 COI communications including half in the final two weeks leading up to adoption of the Final Map on December 14. This rapid increase in testimony challenged the staff and demographers to classify comments for consideration by the Commission.
Possible Solutions: To aid commissioners in classifying and weighing public comment, consider a more structured intake form and testimony guideline for the public along with enhanced methods of aggregating inputs. The California Redistricting Commission’s database of over 30,000 comments was a good example of current technology applied to visibility of public input. It was timely and easily sortable by commissioners and the public.
In a 2013 University of California-Irvine Law paper, “Community of Interest Methodology,” Karin MacDonald and Bruce Cain describe the role of Community of Interest testimony, problems of classification of testimonies, and the potential for “selectivity bias.”
A December 7th Election Law Blog from the University of California-Irvine described a Novel Way of Measuring Communities of Interest. The Center for New Data (CND) has created COI maps derived from a dataset of billions of anonymous cellular device geolocation pings, acquired through partnerships with private vendors, representing approximately 10% of the U.S. population during any given month (approximately thirty-five million unique devices).
Technology will undoubtedly change dramatically before the 2030-31 redistricting cycle. Prioritizing data accessibility will enable the Commission’s decision-making and transparency.