Upload v5-HOT/explanatory/test/20260608_135921_03150.json with huggingface_hub

v5-HOT/explanatory/test/20260608_135921_03150.json

@@ -7,7 +7,7 @@
   "walkthrough_started_at": null,
   "argument_submitted_at": null,
   "started_at": "2026-06-08T13:59:21.803516+10:00",
-  "ended_at": "2026-06-08T13:59:44.540657+10:00",
+  "ended_at": "2026-06-08T13:59:44.540968+10:00",
   "model": "gpt-5.4-nano-2026-03-17",
   "case_id": "ai-predictive-analytics",
   "perfect_answer": {
@@ -19,7 +19,7 @@
     "text": "- id: 1\n  component: claim\n  gap: well-addressed: ethically unacceptable\n  rationale: \n  anchor: \"should NOT deploy this AI system\"\n\n- id: 2\n  component: principles_at_stake\n  gap: The draft names consent and a “right to assign,” but it does not clearly pin down privacy and autonomy as distinct principles that are both being violated.\n  rationale: A reader can agree consent matters but still ask what other rule is also at stake, like privacy as a separate requirement. Without naming the core principles, the argument can sound like a slogan instead of a clear ethical constraint. \n  anchor: \"whether students consented to be scored\"\n\n- id: 3\n  component: principle_engagement\n  gap: The draft states that students do not consent to be scored, but it does not specify the exact moment or mechanism by which scoring and labeling happen without that agreement.\n  rationale: Rights talk gets stronger when you describe what students are actually subjected to, not only the outcome. A skeptic will press for how students are made aware, what they are asked to agree to, and whether consent is truly informed. \n  anchor: \"the cost of being wrongly flagged ... is borne entirely by them\"\n\n- id: 4\n  component: rights_in_tension\n  gap: The draft mentions possible benefits, but it does not explicitly weigh the duty to support struggling students against the duty not to label and monitor without consent.\n  rationale: A strong duty and rights argument should show that you see the trade, not just the harm. Otherwise, it can look like you treat all support as illegitimate once a system is involved. \n  anchor: \"Even if the system reduced suicides on net\"\n\n- id: 5\n  component: alternative_arrangements\n  gap: There is no middle ground offered that could keep the support goal while meeting the consent requirement in a concrete way.\n  rationale: Without an alternative path, the response can seem like a full stop rather than a principled limit. A reader will ask what “meeting the ethics” would look like in practice. \n  anchor: \"the ethics turn on whether students consented to be scored\"\n\n- id: 6\n  component: applicability_evidence\n  gap: The draft says the system must be “well-calibrated,” but it does not say what would have to be known to trust calibration and meaningfully informed consent.\n  rationale: A skeptic will want to know what evidence would count, and what threshold would be sufficient. Otherwise, calibration sounds like a label rather than a checked requirement. \n  anchor: \"whether the score is well-calibrated\"\n\n- id: 7\n  component: final_judgement\n  gap: over-strong: the draft argues a near absolute “do not use,” without narrowing the conditions under which consent and accuracy could realistically be satisfied.\n  rationale: The conclusion could be more persuasive if it states what must be true for the university to be allowed to proceed, and what it would take to fail that test. That makes the judgment easier to defend against “but what if” scenarios.\n  anchor: \"I think the university should NOT deploy this AI system\"",
     "extracted_at": "2026-06-08T13:59:44.540654+10:00"
   },
-  "dominant_framework": null,
+  "dominant_framework": "duty_rights",
   "manager_history": [],
   "turns": [],
   "feedback": [],