Relational Currency in Knowledge Circulation: An Investigation of Representation and Value Conversion

How do representations of contributions and commitments acquire practical significance as they circulate among people, institutions, and digital systems? This paper develops an exploratory framework for examining the movement of evidence-bearing representations and their situated conversion into recognition, cooperation, permissions, and access to productive resources. It introduces relational currency as a provisional analytical term for context-dependent arrangements of presentation, acceptance, and consequential use, while distinguishing these arrangements from money, universal reputation scores, and transferable trust. The analysis separates documentary integrity, factual accuracy, epistemic warrant, institutional recognition, and material return. Thirteen conditional propositions characterize information loss, contextual nonfungibility, binding access constraints, commitment incentives, commons-capacity renewal, and limits of identifying extraction from observed distributions. Historical-materialist discussion examines control of complementary assets, maintenance labor, and the unequal retention of value generated through collective inquiry. The framework is compared with established accounts of credentials, permissions, reputation, relational contracts, and resource allocation, with an empirical model-comparison strategy proposed to assess any additional explanatory value. Sixteen research hypotheses and associated designs specify possible tests. The work provides a conceptual and formal investigation; it reports neither original participant data nor empirically established effects. Its scope remains open to revision through independent proof review, source-level scrutiny, and empirical comparison.

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Publication Details

Journal
Knowledge Commons (Lakehead University)
Published
2026-10-27
DOI
https://doi.org/10.17613/t18yz-cn116
Primary Topic
Research, Science, and Academia
Type
article
Field-Weighted Citation Impact
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article

Relational Currency in Knowledge Circulation: An Investigation of Representation and Value Conversion

Wanhong HUANG
2 links
Knowledge Commons (Lakehead University)
Research, Science, and Academia
article

Relational Currency in Knowledge Circulation: An Investigation of Representation and Value Conversion

Wanhong HUANG
article en

Abstract

How do representations of contributions and commitments acquire practical significance as they circulate among people, institutions, and digital systems? This paper develops an exploratory framework for examining the movement of evidence-bearing representations and their situated conversion into recognition, cooperation, permissions, and access to productive resources. It introduces relational currency as a provisional analytical term for context-dependent arrangements of presentation, acceptance, and consequential use, while distinguishing these arrangements from money, universal reputation scores, and transferable trust. The analysis separates documentary integrity, factual accuracy, epistemic warrant, institutional recognition, and material return. Thirteen conditional propositions characterize information loss, contextual nonfungibility, binding access constraints, commitment incentives, commons-capacity renewal, and limits of identifying extraction from observed distributions. Historical-materialist discussion examines control of complementary assets, maintenance labor, and the unequal retention of value generated through collective inquiry. The framework is compared with established accounts of credentials, permissions, reputation, relational contracts, and resource allocation, with an empirical model-comparison strategy proposed to assess any additional explanatory value. Sixteen research hypotheses and associated designs specify possible tests. The work provides a conceptual and formal investigation; it reports neither original participant data nor empirically established effects. Its scope remains open to revision through independent proof review, source-level scrutiny, and empirical comparison.

Knowledge Commons (Lakehead University)
Openalex Percentile: Top 7%
Research, Science, and Academia
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