Do not simplify the instrument, restructure the interface
Progressive disclosure keeps the full academic apparatus available while keeping the default view clean.
A civic intelligence platform that uses validated instruments like Moral Foundations Theory, wrapped in an experience designed to survive contact with an audience trained on two-minute quizzes.
Interface
What the user touches
Application
Where the rules run
Intelligence
Models and ingestion
Data
What persists
Platform
What it runs on
Online political assessment is dominated by quizzes that place you on a two-axis compass. They spread well and explain almost nothing, because political identity is not two numbers.
The academic instruments that do capture it — Moral Foundations Theory, Schwartz values — are long, dense, and written for research subjects rather than curious people on a phone.
MindPolis exists in the gap: keep the validated instruments intact, and spend the design effort on making a serious assessment something a person will actually finish and want to share.
Rigour that nobody completes measures nothing. The design problem is keeping the instrument intact while making it survive a real audience.
A Turborepo platform pairing a Next.js application with a Python scoring microservice, seeded with a 40-question compass and a 36-question Moral Foundations matrix, rendering results as multidimensional topographies rather than a single point.
Validated instruments
A 40-question compass matrix and a 36-question Moral Foundations Questionnaire, seeded as structured data rather than hardcoded.
Dedicated scoring service
A Python microservice handles scoring, with a TypeScript fallback client so the platform degrades gracefully rather than failing.
Progressive disclosure
Academic layers sit behind "Learn More" toggles — rigour stays available without making the primary surface dense.
Multidimensional visualisation
Radar and polygon mapping via Recharts, in place of a single point on a two-axis grid.
Cognitive signifiers
Gamification built on introspection and rarity rather than XP counters, so the mechanics reinforce reflection instead of speed.
Frictionless sharing
Secure hash routing at /r/[hash] mapped to generated OG images for sharing without exposing identity.
Validated psychometric instruments are long, and length is the primary cause of abandonment.
Simplifying the instrument to raise completion destroys the thing that made it worth taking.
Scoring logic for multiple overlapping frameworks is genuinely complex and does not belong inline in a web app.
Results that cannot be shared do not spread, but sharing political results raises real privacy concerns.
Gamification usually rewards speed, which is the opposite of what a reflective instrument needs.
Every design decision here negotiates the same tension: preserve the instrument, change everything around it.
Progressive disclosure keeps the full academic apparatus available while keeping the default view clean.
A separate Python service isolates the psychometric logic and lets it evolve without touching the application.
The TypeScript fallback client means an unreachable scoring service degrades the product rather than breaking it.
Hash-routed result pages with generated OG images make sharing viable without attaching identity to political data.
Moral Foundations Theory and the compass matrix are used as designed, not trimmed for convenience.
Progressive disclosure, visualisation, and pacing carry the experience so the instrument does not have to be compromised.
Hash routing and generated images allow spread without tying political results to an identity.
Phase 1
Model the compass and MFQ matrices in Prisma and seed them as data, so instruments can change without a rewrite.
Phase 2
Build the Python scoring microservice with a TypeScript fallback client for graceful degradation.
Phase 3
Ship progressive disclosure, radar visualisations, cognitive signifiers, and hash-routed shareable results.
MindPolis is one of the ventures we design, build, and run in-house at AshaVid.