Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
There's no great way to do it but the best result would be to look for people who were top performers and innovators and hire people more like them (or if using it to evaluate resumes, more like the resumes they submitted originally.) You're still going to get input bias for however the human interviewers were biased though... but at least you're getting bias that lead to productive and innovative people being hired. Viewing resumes without any knowledge of how the applicant panned out once hired is basically worthless. You don't hire most people apply, those you do hire don't all stay or perform well long term, etc. Diversity for diversity sake should never be the ideal. Finding the best candidate should always be the ideal.
reddit Cross-Cultural 1539199075.0 ♥ 3
Coding Result
DimensionValue
Responsibilitydeveloper
Reasoningutilitarian
Policynone
Emotionresignation
Coded at2026-04-25T08:33:43.502452
Raw LLM Response
[{"id":"rdc_e7j0k83","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"indifference"},{"id":"rdc_e7izd32","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"fear"},{"id":"rdc_e7j8owp","responsibility":"none","reasoning":"consequentialist","policy":"none","emotion":"approval"},{"id":"rdc_e7j43jz","responsibility":"developer","reasoning":"consequentialist","policy":"none","emotion":"resignation"},{"id":"rdc_e7j52vu","responsibility":"ai_itself","reasoning":"unclear","policy":"unclear","emotion":"unclear"}]