Built an AI-assisted public dashboard grading the Carney government across 11 policy areas and looking for hard feedback on bias, clarity, and trust

Hey Everyone,

I built a public dashboard tracking the federal Carney government across 11 policy areas (housing, climate, defence, ethics, affordability, immigration, etc.). Each dimension gets an A–F grade using a published rubric, with the reasoning and source trail visible on the site.

Live site: https://sawatter.github.io/canada-under-carney/

Built with AI assistance under human editorial direction. That’s disclosed on the site, not hidden. The idea is that if you’re going to publish a political scorecard, the method, reasoning, and sources should be public enough for people to inspect.

I’m not looking for agreement with the grades, and I’m not looking for partisan reactions about whether Carney is good or bad.

What I want to know is: where does the method lose you?

If you spend a few minutes with it, the most useful feedback would be:

1. Which dimension feels least defensible, and why?

2. Can you actually follow how a grade was produced, or where do you lose confidence?

3. What source, metric, or missing context would a skeptical reader expect to see?

I’ve already done a pass tightening threshold language and exposing more of the scoring logic, but I want people to poke holes in what still feels editor-dependent, assumption-driven, or hard to verify.

If one part of it feels weak, biased, confusing, or under-explained, that’s exactly the kind of feedback I want.

Thanks!