The NEW REFLEXIVE LABORATORY Full Corpus

This record publishes the full NEW REFLEXIVE LABORATORY corpus as a Zenodo-native research object. The release is organized around three core components: a human-facing explanatory PDF, a raw reference archive, and an AI-oriented structured scaffold. The explanatory PDF introduces the release architecture and explains how the corpus should be read. The raw reference archive preserves the corpus substrate: 48 article-package ZIP files, 29 transcript TXT files, and one explicitly classified adjacent/non-article object. The archive was built without redactions, transcript normalization, article-package unpacking, or raw-content alteration. The AI structured scaffold provides a machine-facing and advanced-user navigation layer, including registries, inventories, graph and lineage materials, Project Sources operating files, governance notes, claim-boundary rules, research-package derivation guidance, and continuation protocols for future AI-assisted work. The purpose of this release is to make the Reflexive Laboratory inspectable as a process-bearing research corpus rather than only as a sequence of finished papers. In this model, the PDF is the human interface; the reference archive is the raw evidentiary substrate; and the AI scaffold is the structured control surface that helps readers and AI systems navigate the corpus without confusing raw presence with authority. This release does not claim that the corpus is fully normalized, that every raw transcript statement is canonical, or that the AI scaffold replaces human review. Raw transcripts should be interpreted as process records. Article packages should be interpreted in relation to their own manifests, metadata, and release states. The structured scaffold is provided to support reconstruction, reuse, and responsible continuation of the research program.

Authors

Publication Details

Journal
Open MIND
Published
2026-06-19
DOI
https://doi.org/10.5281/zenodo.18902418
Citations
13
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
208.66
Controls
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article

The NEW REFLEXIVE LABORATORY Full Corpus

Peter Bell
13 citations
Open MIND
Scientific Computing and Data Management
208.66
article

The NEW REFLEXIVE LABORATORY Full Corpus

Peter Bell
article en
13 citations

Abstract

This record publishes the full NEW REFLEXIVE LABORATORY corpus as a Zenodo-native research object. The release is organized around three core components: a human-facing explanatory PDF, a raw reference archive, and an AI-oriented structured scaffold. The explanatory PDF introduces the release architecture and explains how the corpus should be read. The raw reference archive preserves the corpus substrate: 48 article-package ZIP files, 29 transcript TXT files, and one explicitly classified adjacent/non-article object. The archive was built without redactions, transcript normalization, article-package unpacking, or raw-content alteration. The AI structured scaffold provides a machine-facing and advanced-user navigation layer, including registries, inventories, graph and lineage materials, Project Sources operating files, governance notes, claim-boundary rules, research-package derivation guidance, and continuation protocols for future AI-assisted work. The purpose of this release is to make the Reflexive Laboratory inspectable as a process-bearing research corpus rather than only as a sequence of finished papers. In this model, the PDF is the human interface; the reference archive is the raw evidentiary substrate; and the AI scaffold is the structured control surface that helps readers and AI systems navigate the corpus without confusing raw presence with authority. This release does not claim that the corpus is fully normalized, that every raw transcript statement is canonical, or that the AI scaffold replaces human review. Raw transcripts should be interpreted as process records. Article packages should be interpreted in relation to their own manifests, metadata, and release states. The structured scaffold is provided to support reconstruction, reuse, and responsible continuation of the research program.

Open MIND
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Scientific Computing and Data Management
208.66
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