Contribution to the handbook
Supporting · Assessed 2026-10-28
The anonymous pairwise-choice format offers a bounded example of presenting policy options. The proposal curation and study sample caveats limit what can be inferred about fairness or broader public preferences.
Does this challenge the goal?
In-scope gap
It asks how one study presented policy choices, a potentially useful detail about citizen-input methods, without contesting the exploration’s goals.
The study’s format does not establish how it would work in governance or represent a wider public.
Why this category?
- background
- alternatives
The evidence reports a study method, not a tested governance mechanism or evidence that the participants represented the broader public.
This is an AI assessment of contribution to the goal, separate from whether the question has an answer.
Making and interpreting laws →
Tests, stop conditions and unresolved work →
Read the exploration goalNew evidence is being assessed. Any answer below is provisional; parts whose evidence changed or was withdrawn are withheld.
Describe the study’s format for presenting policy choices to participants, including how proposals were compared.
What we can say so far
According to the study, volunteers used an online platform to choose between two policy proposals at a time. The proposals were randomly paired, and participation was anonymous.
What remains open
No material gap is recorded within this part’s current scope.
Conditions and limits
- This describes the study’s reported procedure, not whether its volunteers represented the broader public.
Evidence and related ideas
Supporting evidence, qualifications and context play different roles in this answer.
supports
The volunteer policy data The study uses volunteer choices between randomly paired policies from the two leading candidates’ 2022 Brazilian presidential programs. The choices came from an experiment involving collaborative construction of a government program.
States that volunteers chose between randomly paired policies.
Large Language Models (LLMs) as Agents for Augmented Democracy
Read full source: Large Language Models (LLMs) as Agents for Augmented Democracy (opens in a new tab) ↗Read source discussion: Large Language Models (LLMs) as Agents for Augmented Democracy →
supports
Anonymous pairwise comparisons Participants compared two policy proposals at a time on an online platform, and their participation was anonymous.
States that participants compared two proposals at a time online and anonymously.
Large Language Models (LLMs) as Agents for Augmented Democracy
Read full source: Large Language Models (LLMs) as Agents for Augmented Democracy (opens in a new tab) ↗Read source discussion: Large Language Models (LLMs) as Agents for Augmented Democracy →
supports