Evaluating Competitiveness
You can evaluate the competitiveness or responsiveness of a map three different ways in DRA 2020:
All of them depend on the quality of the election data that you use. Absent specific knowledge about a state and the specific elections — or specific goals for your analysis — the best choice is the default election composite.¹
Methodology
To estimate the partisan characteristics of a map, we use:
- A composite of statewide elections, and
- Fractional seat probabilities instead of all-or-nothing accounting, except as noted.
District Statistics
The first way to characterize how competitive a map is (or isn’t) is to simply count the number of districts that fall into the 45–55% range that is generally considered competitive, using the “Partisan Lean” vote shares in district Statistics. In this sample map, two districts are in that range.
A note below the table characterizes the partisan lean and competitiveness. For this sample map, it says “Eight districts lean Republican, three lean Democratic, and two fall in the 45–55% competitive range.”
Analytics View
While that approach is useful for a basic understanding of the competitiveness of a map, it has a significant limitation, because there is no differentiation within the 45–55% range, i.e. there is no difference between a 51% and 55% district even though former is much more competitive than the latter.
The second way to evaluate the competitiveness of a map is using the competitiveness metric in the Competitiveness section of Analytics view which addresses that issue.
In contrast to the first approach, this metric uses a probability distribution to estimate the competitiveness of districts. At 50% vote share for each party, a district is perfectly competitive — a complete toss up with a probability of one — and the tails of the distribution approach zero at 40% and 60% outside of which districts stop having even a small chance of flipping to the other party.
The competitiveness of each district is summed and divided by the total number of districts to get a percentage.
That raw competitiveness is normalized to the range [0–100] where bigger is better, to make it easier to interpret the values.
Advanced View
While that measure of competitiveness is a simple, intuitive concept — especially with the normalized rating — the more academically & judicially accepted measure is call “responsiveness.”²
The third way to assess the responsiveness of a map is Advanced view which includes:
- A seats-votes curve, and
- Three measures of responsiveness
The most common definition of responsiveness is the slope of the seats-votes curve at the statewide vote share.
Each of these approaches has a corresponding approach to evaluating the partisan performance of a map.
Footnotes
- See Election Composites.
- Informally people use “competitiveness” and “responsiveness” as synonyms, but academics consider them quite distinct concepts.
