Contribution to the handbook
Set aside · Assessed 2026-10-28
The example’s participant details and policy choice are study-specific context. The supplied evidence does not show a design implication for a city- or country-scale governance system or a result that would materially change its assessment.
Does this challenge the goal?
None identified
This is a narrow factual question about an example prompt, not a challenge to the definition’s goals, boundaries, or assumptions.
The supplied answer reports the example but does not establish whether the prompt design improved predictions or would be suitable for governance.
Why this category?
- Peripheral study-example detail with no stated effect on system design, alternatives, risks, implementation, or tests.
The question may support understanding the source study, but the supplied packet gives no further governance-design relevance.
This is an AI assessment of contribution to the goal, separate from whether the question has an answer.
New evidence is being assessed. Any answer below is provisional; parts whose evidence changed or was withdrawn are withheld.
Identify the example participant’s details and the two policy proposals presented as the choice.
What we can say so far
The example participant was a 26-year-old liberal man with a master’s degree living in Rio de Janeiro. The choice was between curbing tax evasion and expanding privatization of state-owned companies and infrastructure concessions; he was described as choosing the former.
What remains open
No material gap is recorded within this part’s current scope.
Conditions and limits
- This is the example as reported in the supplied preprint; it is not an independently verified account.
Evidence and related ideas
Supporting evidence, qualifications and context play different roles in this answer.
supports
Portuguese prompt example For a robustness check, the researchers made Brazilian Portuguese prompts describing participant characteristics. The features included age (young or older/“third age”), political ideology (conservative, centrist, or left-wing), urban or rural zone, education (with or without higher education), sex (male or female), and city and state. One example described a 26-year-old liberal man with a master’s degree in Rio de Janeiro choosing a proposal to curb tax evasion over one to expand privatization of state-owned companies and infrastructure concessions.
Directly supplies the participant details and the two policy proposals, including which proposal he chose.
Large Language Models (LLMs) as Agents for Augmented Democracy
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