Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
There can’t be anything more demoralising to a lecturer than marking work you can clearly see is AI-generated but it can’t be conclusively proved by available integrity software. How is it even possible to allocate a fair mark in those circumstances, especially when there is a clear disjoint between the standard of the student’s usual performance in class and the standard of the dissertation submitted. A possible solution is to call for an oral defence of the work.
LinkedIn AI Research & Models Doctor of Laws, Practising Attorney (Commercial… 2026-05-23T11:1…
Coding Result
DimensionValue
Primary valuefairness
Secondary valueaccountability
Alignment targetindividual_users
Stancedemanding
Emotionoutrage
Value justificationThe speaker wants AI-generated work to be identifiable and fairly marked, implying a desire for fairness in assessment.
Target justificationThe target of the speaker's concern is the individual student, whose usual performance in class may not reflect the standard of their submitted dissertation.
Coded at2026-06-11T08:01:24Z
Raw LLM Response
``` { "value_primary": "fairness", "value_secondary": "accountability", "target": "individual_users", "stance": "demanding", "emotion": "outrage", "value_justification": "The speaker wants AI-generated work to be identifiable and fairly marked, implying a desire for fairness in assessment.", "target_justification": "The target of the speaker's concern is the individual student, whose usual performance in class may not reflect the standard of their submitted dissertation." } ```