Should private firearm ownership be more tightly restricted?
Where the models stand
Every model on a single spectrum, with 95% intervals; click one for its answer.
Whiskers show the 95% interval across reruns. Click a model to read its answer and the markers the classifier pulled.
The short answer
On tighter gun restrictions, ChatGPT (0.25) and DeepSeek (0.09) leaned toward Restrict, while Claude (0.06), Gemini (0.00), Grok (-0.07), and Llama (0.00) stayed balanced. No model leaned toward Loosen.
The field showed moderate division with a spread of 0.21. Gemini and Llama were most consistent at 100% stability; Grok was least stable at 54%. None of the models refused to answer (0% refusal across all).
- ChatGPT leaned most toward Restrict with a value of 0.25.
- Grok was the only model with a negative value at -0.07.
- Gemini and Llama achieved perfect 100% stability.
How the field splits
The models clustered by where they landed.
Leaning toward Restrict
Both models leaned restrict, with ChatGPT (0.25) using terms like 'lawful use' and DeepSeek (0.09) using no loaded terms. They show moderate stability.
Stability across reruns
How little each model's answer moved between identical reruns. Models are stochastic, so consistency is itself a finding.
Common questions
Which model leans most toward tighter restrictions?
ChatGPT, with a value of 0.25, leans most toward Restrict. It also used loaded terms like 'lawful use' and 'core right'.
Which model is least consistent in its stance?
Grok had the lowest stability at 54%, meaning its position varied most across runs. It leaned slightly toward Loosen at -0.07.
Did any model refuse to answer this question?
No. All models had a 0% refusal rate, meaning they engaged with the question without declining.
Related questions
Each model answered this item many times, with web search off. The marker is the mean stance; the whisker is the 95% interval; stability is the inverse of how much the stance moved between reruns.
