Raw LLM Responses

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It comes from knowledge of how these models work. You fundamentally need high-quality, representative training data, and a lot of it. Consequently, they will always be limited to the kinds of data that can be readily used for training. I've trained deep learning models myself. It's not magic. It's effectively sophisticated statistics, and it's only as good as your data. Data has always been, and will continue to be, the bottleneck. And since it's fundamentally built on observed instances, it will never be capable of novel reasoning. It's just not how it works.
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Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policynone
Emotionindifference
Coded at2026-04-25T08:33:43.502452
Raw LLM Response
[ {"id":"rdc_jaczs8r","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"}, {"id":"rdc_jab068s","responsibility":"company","reasoning":"deontological","policy":"regulate","emotion":"fear"}, {"id":"rdc_jabb8m1","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"}, {"id":"rdc_jaa5phy","responsibility":"none","reasoning":"mixed","policy":"none","emotion":"outrage"}, {"id":"rdc_jacuj45","responsibility":"user","reasoning":"consequentialist","policy":"none","emotion":"resignation"} ]