Dataset: When the Machine Is Not Enough: An Autoethnography of AI-Assisted Amateur Research and the Boundaries of Epistemic Authority

Replication dataset for a manuscript submitted to AI & Society. This deposit contains coded datasets and tone classification results supporting an autoethnographic study of AI-assisted amateur research. An emergency medicine physician used ChatGPT-4o as an epistemic collaborator for three research projects (Collatz conjecture, cosmology, STS). All manuscripts were rejected after peer review. Core dataset: 2,566 unique assistant messages across 47 conversations, classified into four tone categories (E/C/M/N) via full census using Claude Opus 4. v3 update: Iterative calibration with refined criteria, v2 re-coding of all messages, and IRR verification (κ=0.557, 83.6% agreement). Key findings: E:C=3.2:1 overall; Collatz 1.1:1, ITC 4.6:1, CST 2.6:1. 172 files in full_census_v2.zip including raw data, v1/v2 classifications, input batches, and IRR validation files.v4 (2026-03-17): Added R analysis scripts (phase1_conversation_structure.R, phase1_critical_moments.R) and calibrated datasets (conversation_summary_calibrated.csv, sycophancy_trajectory_calibrated.csv, critical_moments.csv) for full reproducibility of the tone classification analysis reported in the manuscript.