Bridge Studies in Applied Epistemology: Thirteen Comparative Analyses Linking Classical Philosophy of Science to Foundation-Model Methodology

This restricted bundle contains thirteen bridge studies linking a methodological research programme on foundation-model-mediated terminology engineering to canonical traditions in philosophy of science and applied epistemology. The studies address: a multi-tradition integrative reading of Wittgenstein, Polanyi, Dennett, Friston, and Schmidhuber-Hutter in relation to measurement and comparison across language-model systems; Thomas Kuhn paradigm theory and pre-paradigmatic status of emerging methodological fields; Imre Lakatos research programmes and progressive problem-shifts; Gaston Bachelard epistemological obstacles and the rupture between empirical and scientific knowledge; Karl Popper falsifiability criterion and its complementary relationship to upstream formulation disciplines; John Ioannidis metaresearch findings on systematic bias, replication, and transparency in research practices; Susan Leigh Star and James Griesemer boundary objects and their role in cross-corpus knowledge transfer; Rudolf Carnap explication method and its application to ISO-704-aligned term definition; Maria Teresa Cabre terminology theory and neology in specialised communication; Peter Galison trading zones and intercalation as models for cross-disciplinary integration; Bruno Latour actor-network theory applied to human-AI research collectives; FAIR principles in open science as a normative framework for terminology corpus management; and Mona Simion and Christoph Kelp functionalist conceptual engineering framework as an evaluative discipline for terminology work. All bridge studies are independent research hypotheses produced without institutional affiliation or peer review, shared under CC BY-NC-ND 4.0. Part of the AUGMANITAI Research Programme working corpus (concept-DOI 10.5281/zenodo.20161494). Living document; prepared with AI assistance. All cited works are referenced in good faith for scholarly discussion; any citation requiring source-level confirmation is flagged within the restricted files. AI-transparency (EU AI Act, Art. 50): prepared with substantial large-language-model assistance; all content reviewed and validated by the human author, who retains sole responsibility.