AUGMANITAI Field Foundation Bundle 9 - Concept Mining: Multi-Disciplinary Lens Application across the AUGMANITAI Research Program (Redacted Derivative Compilation, April 2026)

Forensic prior-art deposit. Restricted access. Redacted derivative compilation. The bundle compiles 46 markdown documents produced 2026-04-29 by an internal multi-agent concept-mining workflow operated by the depositor. Each document applies a specific disciplinary lens (linguistics, phenomenology, hermeneutics, semiotics, cognitive science, mathematics, philosophy of science, sociology, anthropology, history, political theory, ethics, AI safety, sport science, decision theory, network theory, information theory, neuroscience, AGI theory) to a specific source domain within the AUGMANITAI / NEOMANITAI / PERMANITAI research program. Redaction notice: the deposited documents are redacted derivatives. Specific markers, sections, and term-occurrences have been removed or substituted by an automated redaction pass per the AUGMANITAI 26-paragraph Disclaimer V4 (notably Sec. 6 medical-privacy, Sec. 17 commercial-boundary, Sec. 13 author-validation-scope). Original (unredacted) source documents remain in the depositor's local infrastructure and are not part of this deposit. The bundle README documents the redaction in full. Multi-layer hash anchoring (SHA-256 + SHA-512 + SHA3-256 + SHA3-512 + BLAKE3) plus Bitcoin OpenTimestamps stamping on the parent manifest. Per Sec. 17 of the Disclaimer below, no commercial offer or solicitation is intended. Per Sec. 12, AI-assistance is disclosed; per Sec. 13, the redacted derivative form deposited here is the depositor's curated artifact for restricted prior-art-anchor purposes. Researchers seeking access for legitimate scholarly purposes may contact the depositor via ORCID-linked channels (ORCID 0009-0006-3773-7796). Anchored as supplement to DOI 10.5281/zenodo.19904045 (Field Foundation Bundle 8 - External AI Synthesis on Bidirectional Language as Code, 2026-04-30) and DOI 10.5281/zenodo.19691495 (Compression Axiom canonical statement, 2026-04-22). AUGMANITAI 26-Paragraph Disclaimer V4 (English, full text) §1 Descriptive Nature (D): All content within the AUGMANITAI framework, including all terminological definitions, term descriptions, framework descriptions, performance factor analyses, substrate tables, and research hypotheses, is exclusively descriptive (D). Every statement documents observed or proposed phenomena without expressing any normative position regarding how things should be. §2 No Recommendation: No content within this framework constitutes, implies, or should be interpreted as a recommendation for any specific action, behavior, technology adoption, product selection, organizational change, investment, career decision, or personal choice. Readers are solely responsible for their own decisions. §3 No Instruction: This framework does not instruct anyone to do anything. No content should be interpreted as a set of instructions, a how-to guide, a tutorial, a training manual, or an operational protocol. All content describes what has been observed, not what should be done. §4 No Advice: No content within this framework constitutes professional advice of any kind, including but not limited to business advice, career advice, technology advice, organizational advice, strategic advice, personal advice, educational advice, or any other form of guidance. This is a research framework, not a consultancy. §5 No Normative Position: The AUGMANITAI framework takes no normative position on any matter. It does not express, imply, or endorse any view about what is right, wrong, better, worse, preferable, or optimal. All evaluative language, where present, describes observed patterns and proposed hypotheses, not the author's normative stance. §6 No Medical Position: No content within this framework constitutes, implies, or should be interpreted as medical information, medical advice, medical diagnosis, medical treatment recommendation, or medical opinion. Terms that describe cognitive, perceptual, or affective phenomena are terminological descriptions for research purposes, not medical or clinical assessments. §7 No Therapeutic Position: No content within this framework constitutes, implies, or should be interpreted as therapeutic advice, therapeutic intervention, psychotherapeutic guidance, counseling, or any form of mental health treatment. Any resemblance to therapeutic concepts is incidental to the terminological description of observed phenomena. §8 No Diagnostic Position: No content within this framework constitutes, implies, or should be interpreted as a clinical diagnosis, psychological assessment, cognitive evaluation, or any form of diagnostic instrument. Performance factor analyses describe research constructs, not clinical diagnostic categories. §9 No Legal Position: No content within this framework constitutes, implies, or should be interpreted as legal advice, legal opinion, legal analysis, regulatory guidance, compliance advice, or any form of legal counsel. References to legal frameworks (such as the EU AI Act) are descriptive and do not constitute legal interpretation. §10 No Moral Position: No content within this framework constitutes, implies, or should be interpreted as a moral judgment, ethical prescription, or philosophical position about what is morally right or wrong. Ethical observations within the framework are descriptive accounts of observed phenomena, not moral imperatives. §11 Academic and Research Purposes: All content within this framework is intended exclusively for academic discourse, scientific research, scholarly communication, and educational purposes within the research community. This is a research project contributing to the scientific understanding of human-AI interaction, not a commercial product or service. §12 AI Assistance Disclosure: Content within this framework was developed with the assistance of artificial intelligence systems, including large language models. The author used AI tools as research instruments for systematic observation, documentation, and formalization of interaction phenomena. AI-generated content has been reviewed, validated, edited, and curated by the human author. §13 Author Review and Validation: All terms, definitions, framework descriptions, performance factor analyses, and research hypotheses have been individually reviewed, validated, and published by the author, Andreas Ehstand. The author assumes responsibility for the published content in its capacity as a descriptive research framework. §14 Age Restriction (18+): All content within this framework is intended for users who are 18 years of age or older. The terminological descriptions address complex cognitive, psychological, and interaction phenomena that require mature interpretation within an academic context. §15 Independent Academic Project: The AUGMANITAI framework, including PFT-MKI (Performance Factor Theory of Human-AI Interaction), ROBMANITAI, Neomanitai, and all associated publications, is an independent academic research project. It is not affiliated with, endorsed by, or sponsored by any university, corporation, government agency, or other institution unless explicitly stated otherwise. §16 No Professional Service: No content within this framework constitutes, implies, or should be interpreted as a professional service, consulting engagement, coaching service, training program, workshop offering, or any form of professional service delivery. The framework is published as open-access research, not as a service. §17 No Offer: No content within this framework constitutes, implies, or should be interpreted as a commercial offer, business proposal, service offering, product launch, sales pitch, or invitation to enter into any commercial relationship. The framework is a research publication, not a commercial communication. §18 No Commercial Product: The AUGMANITAI framework is not a commercial product. It is not software, not a platform, not a tool, not an application, and not a service for sale. It is a published academic research framework made available under a Creative Commons license for research and educational purposes. §19 Empirical Claims Subject to Peer Review: All empirical claims, research hypotheses, observed patterns, and proposed frameworks within this project represent the current state of the author's research. They are formulated as testable, falsifiable propositions subject to peer review, replication, revision, and potential refutation through further empirical investigation. No claim of absolute truth, completeness, or finality is made. §20 Rights Reserved for Future Changes: The author reserves all rights regarding future modifications, updates, extensions, corrections, retractions, versioning, or discontinuation of any content within this framework. §21 License (CC BY-NC-ND 4.0): All content is published under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Attribution required, commercial use prohibited, derivative works not permitted. §22 Bilingual Publication (EN + DE): This framework is published bilingually in English and German. §23 Research Purpose Statement: This terminological framework describes observed phenomena in human-AI interaction for academic research purposes. Terms describing interaction patterns are documented in the same descriptive spirit as medical terminology documents pathologies, criminological terminology documents criminal behavior, and cybersecurity terminology documents attack vectors: for the purpose of understanding, diagnosis, classification, and prevention - not for instruction, facilitation, or encouragement of any harmful behavior. §24 Misuse Exclusion: Any use of this terminology, these frameworks, these performance factor models, or any associated content for the purpose of manipulating, deceiving, exploiting, surveilling, coercing, or harming humans, AI systems, organizations, or any other entity is explicitly outside the intended scope of this research. Such use is condemned by the author. §25 Safety Intent Statement