Extended restricted snapshot (v4) of the AUGMANITAI / NEOMANITAI research bundle. Author: Andreas Ehstand, independent researcher, Starnberg, Germany. ORCID 0009-0006-3773-7796. Wikidata Q138634675. This version extends the v3 snapshot with three further companion papers that deepen specific aspects of the Explicitation Protocol and its surrounding theory. All three are full-length restricted research papers with the complete 26-paragraph bilingual disclaimer (V4.0) appended. Paper D — The Tool, Not the Answer: Distinguishing Concept Elicitation from Response Generation. 16 pages, 6,800+ words. Addresses a frequent misreading of the explicitation protocol by specifying the four registers in which concept elicitation categorically differs from ordinary response generation: direction of search (inward vs outward), form of output (structured primitive vs unstructured response), persistence (accumulating primitive layer vs single-use artefact), and role of the human interlocutor (framing agent vs consumer). Synoptic table, four-question practical guide for mode selection, consequences for evaluation. Paper E — Second-Order Emergence: The Generative Dynamics of Named Concepts Within Accumulating Primitive Layers. 16 pages, 6,900+ words. Characterises the phenomenon by which primitives within a maturing primitive layer produce further content through combination, attraction, and perceptual reframing. Three-level taxonomy of accessible content (unnamed known, unnamed unknown, newly emergent). Three structural limits (training-bound yield, framing-dependent quality, verification requirement). Practical implications for layer-building. Honest acknowledgement of open questions. Paper F — Multi-Perspective Analysis: Ontological, Epistemological, Systems-Theoretic, Phenomenological, Linguistic-Philosophical, and Cosmological Readings. 17 pages, 7,300+ words. Examines the explicitation protocol through six disciplinary perspectives, each contributing a distinct structural observation. The protocol produces a new category of entity (articulated forms); generates structured hypotheses with calibrated confidence; operates as a structurally-coupled self-elaborating process; enriches practitioners' self-access without replacing practice; extends the boundaries of the structurally expressible; belongs to a family of instruments that extend articulated access to structural regularities in the world. Synoptic conclusion; stated boundaries of the analysis. Central claim, carried across all three papers. The explicitation protocol is a categorically distinct mode of using learning systems, whose outputs interact generatively within accumulating primitive layers, and whose structural significance spans ontological, epistemological, systems-theoretic, phenomenological, linguistic-philosophical, and cosmological dimensions. The papers develop these claims structurally, without speculation about historical adoption, without recommendation for particular uses, and without evaluative framing. Methodological provenance. The underlying decomposition discipline originates in Leistungsfaktorenanalyse (performance-factor analysis) as practiced at ITF-tour and Bundesliga-level tennis coaching and has been transferred to representation-capable artificial systems under the wider research designation PERMANITAI. The existing empirical record consists of 5,524 ISO-aligned intensional definitions with 50,653 SKOS-compliant semantic relations across 274 specialist fields, produced over nine months. Complete series to date. Technical Paper (10.5281/zenodo.19691489), Mathematical Foundations (10.5281/zenodo.19691491), public Concept statement (10.5281/zenodo.19691495), Explicitation Protocol v2 (10.5281/zenodo.19701316), Extended Series v3 with Papers A, B, C (10.5281/zenodo.19701432). This v4 deposit adds Papers D, E, F. Prior files from v1, v2, v3 are retained unchanged. Access. Restricted. Requests are evaluated individually. Contact via the author's ORCID record. Legitimate research, review, or legal parties are welcome. License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). Record date: 23 April 2026. AUGMANITAI 26§ Full Disclaimer — Bilingual (EN + DE) — Version 4.0 For use on: Zenodo, GitHub, GitHub Pages, HuggingFace, npm, PyPI, LinkedIn, Medium, ORCID, Wikidata, all publications and platforms Disclaimer / Haftungsausschluss English (EN) §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
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Andreas Ehstand
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Andreas Ehstand (Thu,) studied this question.
www.synapsesocial.com/papers/69eb0a94553a5433e34b4936 — DOI: https://doi.org/10.5281/zenodo.19701495
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