Primary Evidence for "The Epistemic Singularity": Raw Prompts and Verbatim Transcripts from Generative AI Stress‑Tests (February 2026) by Jalal Khawaldeh

This dataset contains the complete primary evidence used in Appendices A and B of the dissertation The Epistemic Singularity: Scientific Rationality After Generative AI. It includes: Raw experimental prompts (Appendix A), reproduced verbatim. Full transcripts of all interactions with three generative AI systems—OpenAI ChatGPT‑Scholar (GPT‑4 architecture), DeepSeek‑R1, and Microsoft Copilot (GPT‑4‑Turbo backend)—generated between January and February 2026. Metadata documenting system versions, timestamps, and interaction context. These materials serve as archival documentation of the epistemic stress‑tests conducted in the dissertation. They illustrate structural epistemic dynamics such as opacity, synthetic recombination, explanatory theater, hyper‑acceleration, and epistemic displacement. The dataset is intended to ensure long‑term reproducibility, transparency, and scholarly verification of the empirical illustrations discussed in the dissertation. All transcripts are reproduced verbatim, including any typographical or formatting irregularities present in the original outputs. Screenshots of all interactions are archived by the author and available upon request. Contents: Prompts_Feb2026.pdf — Raw prompts used in the epistemic stress‑tests Transcripts_Feb2026.pdf — Verbatim transcripts of all nine interactions Metadata_Feb2026.txt — System versions, timestamps, and contextual notes

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-03
DOI
https://doi.org/10.5281/zenodo.18844909
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Primary Evidence for "The Epistemic Singularity": Raw Prompts and Verbatim Transcripts from Generative AI Stress‑Tests (February 2026) by Jalal Khawaldeh

Jalal Khawaldeh
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Primary Evidence for "The Epistemic Singularity": Raw Prompts and Verbatim Transcripts from Generative AI Stress‑Tests (February 2026) by Jalal Khawaldeh

Jalal Khawaldeh
article en

Abstract

This dataset contains the complete primary evidence used in Appendices A and B of the dissertation The Epistemic Singularity: Scientific Rationality After Generative AI. It includes: Raw experimental prompts (Appendix A), reproduced verbatim. Full transcripts of all interactions with three generative AI systems—OpenAI ChatGPT‑Scholar (GPT‑4 architecture), DeepSeek‑R1, and Microsoft Copilot (GPT‑4‑Turbo backend)—generated between January and February 2026. Metadata documenting system versions, timestamps, and interaction context. These materials serve as archival documentation of the epistemic stress‑tests conducted in the dissertation. They illustrate structural epistemic dynamics such as opacity, synthetic recombination, explanatory theater, hyper‑acceleration, and epistemic displacement. The dataset is intended to ensure long‑term reproducibility, transparency, and scholarly verification of the empirical illustrations discussed in the dissertation. All transcripts are reproduced verbatim, including any typographical or formatting irregularities present in the original outputs. Screenshots of all interactions are archived by the author and available upon request. Contents: Prompts_Feb2026.pdf — Raw prompts used in the epistemic stress‑tests Transcripts_Feb2026.pdf — Verbatim transcripts of all nine interactions Metadata_Feb2026.txt — System versions, timestamps, and contextual notes

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 38%
Artificial Intelligence in Healthcare and Education
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Primary Evidence for "The Epistemic Singularity": Raw Prompts and Verbatim Transcripts from Generative AI Stress‑Tests (February 2026) by Jalal Khawaldeh — Jalal Khawaldeh · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS