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📄 Abstract
Abstract: Urban assessments often compress diverse needs into single scores, which can
obscure minority perspectives. We present a community-centered study in
Montreal (n=35; wheelchair users, seniors, LGBTQIA2+ residents, and
immigrants). Participants rated 20 streets (accessibility, inclusivity,
aesthetics, practicality) and ranked 7 images on 12 interview-elicited
criteria. Disagreement patterns were systematic in our sample: wheelchair users
diverged most on accessibility and practicality; LGBTQIA2+ participants
emphasized inclusion and liveliness; seniors prioritized security. Group
discussion reduced information gaps but not value conflicts; ratings conveyed
intensity, while rankings forced trade-offs. We then formalize negotiative
alignment, a transparent, budget-aware bargaining procedure, and pilot it with
role-played stakeholder agents plus a neutral mediator. Relative to the best
base design under the same public rubric, the negotiated package increased
total utility (21.10 to 24.55), raised the worst-group utility (3.20 to 3.90),
improved twentieth percentile satisfaction (0.86 to 1.00; min-max normalized
within the scenario), and reduced inequality (Gini 0.036 to 0.025). Treating
disagreement as signal and reporting worst-group outcomes alongside totals may
help planners and AI practitioners surface trade-offs and preserve minority
priorities while maintaining efficiency.