All Seven Machine Psychology Preprints Now Fully Open: Data, Code, and Coverage Update

Oct 20, 2026·
Abbas Hamidavi
Abbas Hamidavi
· 1 min read
Fully open data, code, and international coverage
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Two updates on the Machine Psychology corpus (seven preprints, all published on Research Square in July 2026 under CC-BY 4.0):

1. Full open-data coverage

All core datasets, raw transcripts, codebooks, and analysis pipelines are now public on the Open Science Framework:

  • Ten Novel Phenomena in Machine Psychology, OSF and Mendeley Data (DOI: 10.17632/h76chwbx83.1)
  • Algorithmic Gaslighting (RDI coding rubric, blind codebook, 15 multi-turn transcripts), OSF + code
  • The Lie Awareness Spectrum (L0–L5 protocols), OSF + code
  • Thinking Behind the Mask (15 experiments, 199+ item governance library), OSF
  • Ontological Firewalls (OAPD protocol, 24 experimental runs), OSF

Anyone can now replicate the statistical results end to end.

2. Growing international coverage and indexing

Since July, the corpus has been independently summarized, reviewed, and indexed, including:

  • A full explainer on gist.science (link)
  • A critical review in the Synthetic Personality Review
  • Multiple entries on ecoruspace.me, a Russian-language science-news aggregator
  • Indexing in the SwarmLabs / GeneTech Chinese AI Safety & Alignment knowledge engine (data.swarmlabs.tools) under AI safety and alignment keywords
  • All seven preprints indexed on alphaXiv, DeepDyve, Sciety, scite.ai, and ResearchGate

Thank you to everyone who has read, discussed, and shared this work. The next milestone I am most excited about: the revised manuscript of Ten Novel Phenomena in Machine Psychology, now submitted to AI and Ethics (Springer Nature).

Abbas Hamidavi
Authors
CS Student & AI Researcher Open Science advocate Building tools to probe, analyze, and secure LLM architectures Exploring the intersection of Red Teaming and Interpretability. AI Safety Researcher at Islamic Azad University, Mashhad, running an independent research programme in Machine Psychology. ORCID: https://orcid.org/0009-0001-7342-7844