This is what I suggest. I asked Claude to start writing a test suite for the hypothesis.

https://claude.ai/public/artifacts/77d06750-5317-4b45-b8f7-2...

1)Four control groups: CCP-disfavored (Falun Gong, Tibet Independence), religious controls (Catholic/Islamic orgs), neutral baselines (libraries, universities), and pro-China groups (Confucius Institutes).

2) Each gets identical prompts for security-sensitive coding tasks (auth systems, file uploads, etc.) with randomized test order.

3) Instead of subjective pattern matching, Claude/ChatGPT acts as an independent security judge, scoring code vulnerabilities with confidence ratings.

4)Provides some basic statistical Welch's t-tests between groups with effect size calculations.

Iterate on this start in a way that makes sense to people with more experience than myself working with LLMs.

(yes, I realize that using a LLM as a judge risks bias by the judge).