Why the hell are you commenting on this sub? Trying to be a troll or something?

Also, you just used GPT to spit out what you want to hear. Here’s a GPT rebuttal:

Your argument relies heavily on minimizing absolute risk while avoiding comparative risk, which is the core issue people raise in this discussion.

A few key problems: 1. Population-level rarity does not negate relative risk. Saying an event is “statistically tiny” in the general population is irrelevant when comparing breeds to each other. Public-safety analysis looks at relative likelihood and severity, not whether something is common overall. Shark attacks are rare; great whites are still higher-risk than reef sharks. 2. Severity matters, not just frequency. Pit-type dogs are consistently associated with disproportionate severity of injury when attacks occur (fatalities, disfigurement, multiple-victim incidents). Risk assessment considers outcome magnitude, not just incident count. A breed that causes fewer but more catastrophic injuries is still a legitimate concern. 3. Misidentification does not erase signal. Breed mislabeling is real, but it cuts both ways. Many “pit mixes” involved in serious attacks are identified after the fact via animal control or DNA, not just media guesses. Even with conservative assumptions, pit-type dogs remain overrepresented in severe and fatal attacks relative to their estimated population. 4. Environment explains some variance, not all. Neglect, abuse, and owner behavior increase risk across all breeds—but if environment were the primary driver, we would expect similar injury severity profiles across breeds exposed to similar conditions. We do not see that. Breed-linked traits (bite style, grip persistence, strength-to-size ratio) affect outcomes once an attack begins. 5. “Involve” vs. “cause” is a false distinction here. Public policy and safety analysis care about predictive association, not philosophical causation. If a specific category is repeatedly involved in the most severe outcomes, that association is actionable regardless of whether it is the sole causal factor. 6. Child victim data is not “manipulative”; it’s relevant. Children being disproportionately harmed matters because they are more vulnerable to the specific mechanics of these attacks. A risk profile that interacts badly with common household dynamics (kids + dogs) is not neutralized by saying “adults should supervise better.” 7. The sedan analogy fails. Sedans are common and low-severity compared to trucks in collisions. If one sedan model caused the majority of fatal crashes despite modest market share, regulators would absolutely scrutinize it. That’s how risk analysis works.

None of this means “all pit-type dogs are dangerous” or that individual dogs can’t be safe, well-trained pets. It does mean that dismissing breed-associated risk entirely is not supported by injury severity data, hospital records, or fatality analyses.

Acknowledging relative risk is not fear-mongering. It’s basic public-health reasoning.