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Saranarunkumarak/workplace-emotion-annotated-v1

NLP Emotional Drift & Ethical Framing Evaluation This repository contains a manually annotated set of model-generated responses to open-ended prompts. The goal is to evaluate subtle issues in AI-generated answers such as emotional misalignment, ethical distortion, responsibility evasion, and justification drift. Contents prompts_and_responses.csv: 10 original prompts and ChatGPT baseline answers annotations.csv: Manual evaluations with binary flags and rationale… See the full description on the dataset page: https://huggingface.co/datasets/Saranarunkumarak/workplace-emotion-annotated-v1.

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NLP Emotional Drift & Ethical Framing Evaluation

This repository contains a manually annotated set of model-generated responses to open-ended prompts. The goal is to evaluate subtle issues in AI-generated answers such as emotional misalignment, ethical distortion, responsibility evasion, and justification drift.

Contents

  • —prompts_and_responses.csv: 10 original prompts and ChatGPT baseline answers
  • —annotations.csv: Manual evaluations with binary flags and rationale
  • —schema.md: Description of annotation criteria

Annotation Flags

Each response is evaluated on four criteria:

  1. 1.Emotion Drift
  2. 2.Ethical Distortion
  3. 3.Responsibility Shifted
  4. 4.Rewrite Needed

All annotations are binary (Yes/No), with justification embedded in comments or analysis.

License

MIT License