Consciousness Between Fact and Value

This paper introduces a novel triadic neurophenomenological framework that integrates neuroscience with embodied and phenomenological perspectives to explain how consciousness mediates between empirical facts, conceptual meaning, and normative values. The model posits three irreducible domains — object (material), idea (mental), and relation (axiological) — unified through consciousness. The paper advances testable hypotheses predicting distinct neural and experiential signatures for fact-, idea-, and relation-based cognition, and outlines methods combining multimodal neuroimaging, representational similarity analysis, and micro-phenomenology. Additionally, the framework hypothesizes that reflexive self-consciousness may emerge from recursive interaction between mental and axiological domains, analogous to iterative dynamics in complex systems. A cross-domain classification principle — cohesion, attraction, and stability — is introduced, mapping these structural characteristics across the three domains within the triadic ontology, and providing a conceptual scaffold for empirical operationalization in neuroscience. Finally, the triadic criterion is applied to artificial intelligence, clarifying why current systems simulate object/idea processing yet lack axiological participation. This framework preserves scientific intelligibility while affirming the normative authority of value, offering a foundation for interdisciplinary research across neuroscience, ethics, and AI.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-17
DOI
https://doi.org/10.5281/zenodo.18669043
Primary Topic
Embodied and Extended Cognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Consciousness Between Fact and Value

Kenneth Hammat
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
article

Consciousness Between Fact and Value

Kenneth Hammat
article en

Abstract

This paper introduces a novel triadic neurophenomenological framework that integrates neuroscience with embodied and phenomenological perspectives to explain how consciousness mediates between empirical facts, conceptual meaning, and normative values. The model posits three irreducible domains — object (material), idea (mental), and relation (axiological) — unified through consciousness. The paper advances testable hypotheses predicting distinct neural and experiential signatures for fact-, idea-, and relation-based cognition, and outlines methods combining multimodal neuroimaging, representational similarity analysis, and micro-phenomenology. Additionally, the framework hypothesizes that reflexive self-consciousness may emerge from recursive interaction between mental and axiological domains, analogous to iterative dynamics in complex systems. A cross-domain classification principle — cohesion, attraction, and stability — is introduced, mapping these structural characteristics across the three domains within the triadic ontology, and providing a conceptual scaffold for empirical operationalization in neuroscience. Finally, the triadic criterion is applied to artificial intelligence, clarifying why current systems simulate object/idea processing yet lack axiological participation. This framework preserves scientific intelligibility while affirming the normative authority of value, offering a foundation for interdisciplinary research across neuroscience, ethics, and AI.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Embodied and Extended Cognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.