Systematic Neology: Evaluating When New Terms Help in Human-AI Work

This conceptual working paper reconstructs Systematic Neology as a bounded programme on the justification, interpretation and revision of candidate terms in human-AI work. Its central comparison asks whether a proposed name adds value beyond adequate existing language and the same explanation without the name. Eight revisable methodological commitments, six record types, seven relations, three invented illustrations and four research questions make the proposal inspectable. The paper distinguishes this focused question from Semanturgy and Cognitive Continuity Methodology and acknowledges established conceptual and terminological work. Historical local and archived sources differ in umbrella wording; they are not presented as identical or as evidence of earlier public access. The earlier restricted record remains separate and unchanged. English paper with German abstract, conceptual model JSON, README and SHA-256 manifest. No empirical findings, established new discipline, global novelty, complete literature review or ISO conformity are claimed. Publication, external retrieval and model-parameter change remain distinct. Drafting and editorial checks were AI-assisted; no external peer review or personal sentence-by-sentence author review is asserted. This new open edition omits technical source procedures and internal provenance files.