Distinguishing Interpretive Uptake from Dynamical Influence in Generative Relational Models of Social Meaning

A signal can change an interpreter's trajectory through heat, salience, coercion or understood content. A general relational dynamics accommodates these possibilities while leaving their semantic differences open. This paper develops a proposed bridge between labelled consequence profiles and claims about interpretive uptake. It distinguishes reference, inferential use, practical significance and institutional force, together with episode uptake, correctness and action. Matched contrasts expose content–nuisance confounding. Conditional identification results characterize the semantic roles compatible with a declared model family and show how additional tests refine that set. A finite-test construction establishes a precise limit on unrestricted extrapolation. An interactive extension separates evidence about an earlier interpretation from formation of a present interpretation, and an exact state-elimination derivation exhibits retained organization and local memory. Shared request and institutional-token examples compare the warrants required by different semantic targets. Verified communication, communicative-intention and grounding accounts supply antecedents and disagreements. The philosophical argument treats semantic bridges themselves as revisable objects of public criticism, especially where correctness standards and opportunities to respond are unequally controlled. A prospective study specifies contrasts, rival explanations and counterconditions. The resulting position supports scoped semantic attribution while preserving the distinction between mathematical identification, conceptual warrant and empirical validation.

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Publication Details

Journal
Knowledge Commons (Lakehead University)
Published
2026-09-14
DOI
https://doi.org/10.17613/erqt9-e0j92
Primary Topic
Child and Animal Learning Development
Type
article
Field-Weighted Citation Impact
0.00
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Distinguishing Interpretive Uptake from Dynamical Influence in Generative Relational Models of Social Meaning

Wanhong HUANG
Knowledge Commons (Lakehead University)
Child and Animal Learning Development
article

Distinguishing Interpretive Uptake from Dynamical Influence in Generative Relational Models of Social Meaning

Wanhong HUANG
article en

Abstract

A signal can change an interpreter's trajectory through heat, salience, coercion or understood content. A general relational dynamics accommodates these possibilities while leaving their semantic differences open. This paper develops a proposed bridge between labelled consequence profiles and claims about interpretive uptake. It distinguishes reference, inferential use, practical significance and institutional force, together with episode uptake, correctness and action. Matched contrasts expose content–nuisance confounding. Conditional identification results characterize the semantic roles compatible with a declared model family and show how additional tests refine that set. A finite-test construction establishes a precise limit on unrestricted extrapolation. An interactive extension separates evidence about an earlier interpretation from formation of a present interpretation, and an exact state-elimination derivation exhibits retained organization and local memory. Shared request and institutional-token examples compare the warrants required by different semantic targets. Verified communication, communicative-intention and grounding accounts supply antecedents and disagreements. The philosophical argument treats semantic bridges themselves as revisable objects of public criticism, especially where correctness standards and opportunities to respond are unequally controlled. A prospective study specifies contrasts, rival explanations and counterconditions. The resulting position supports scoped semantic attribution while preserving the distinction between mathematical identification, conceptual warrant and empirical validation.

Knowledge Commons (Lakehead University)
Creative Commons (US)
Reduced inequalities
Openalex Percentile: Top 5%
Child and Animal Learning Development
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