Sortition, the random selection of individuals to form deliberative panels, has seen a renaissance in recent years, as institutions realise the value of direct community and stakeholder input in deliberation and policymaking. These panels improve the quality of outcomes, increase public trust and engagement, and create more inclusive processes. Yet little attention has been paid to whether panels preserve a community's intersectional structure -- how demographic traits combine -- rather than only its marginal proportions. This thesis uses a simulated sortition pipeline (population, survey sample, and panel selection via the LexiMin algorithm) to test whether quota-constrained selection preserves the joint two-variable association present in a survey sample. Across all simulated conditions, effectively every feasible panel showed a two-variable relationship significantly different from its sample, at a rate far exceeding simple random sampling. These findings motivated Intersection Inspector, a diagnostic Shiny app helping practitioners assess a panel's representativeness before deliberation begins.
Keywords: sortition; citizens' assemblies; representativeness; intersectionality; panel selection algorithms
https://ebsmonash.shinyapps.io/intersection_inspector/
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
The Intersection Inspector app code (scripts/intersection_inspector/) is licensed separately under the GNU Affero General Public License v3.0, which requires anyone who modifies and runs the app as a network service to make their modified source available to its users.