The Meta-Representational Preemption Principle (MRPP) A Conditional Framework for Self-Referential Priority Shifts in Retrieval and Selection Systems

This paper proposes the Meta-Representational Preemption Principle (MRPP), a conditional theoretical framework for examining situations in which a representation of a selection process may become accessible before the target items that the process was intended to select. The framework originates from a primary case in which an individual establishes a rule for which of two or more thoughts should be recalled first. During a subsequent recall attempt, the individual may instead become aware of the competition rule, the prior commitment, or the process of determining which thought will appear first. This process-related representation was not included in the original candidate set, yet it may become the first consciously available content.The paper formalizes this case as the Self-Referential Recall-Preemption Case (SRRPC). It distinguishes candidate-set membership, activation, conscious availability, reported first occurrence, and subsequent behavioral influence. The proposed mathematical architecture includes candidate-set notation, threshold-crossing times, a conditional preemption indicator, candidate activation dynamics, a probabilistic first-choice model, and an information-theoretic description of uncertainty. It then examines possible recursive structures, boundary conditions, cross-domain analogies, competing explanations, and falsifiable empirical predictions.The framework is intended to be medium-independent only in a conditional structural sense: its proposed mechanism may be investigated in any system where a defined candidate set, a representation of the selection process, and a shared priority or access mechanism can be independently identified. Such generality is a research hypothesis, not an established universal law. The equations are candidate formal models rather than validated descriptions of human neurobiology. No empirical results are claimed. The principal objective is to transform the original conceptual observation into an operationally defined, mathematically explicit, and potentially falsifiable research program.Keywords: metacognition; self-reference; memory retrieval: priority competition; candidate-set divergence; attentional selection; dynamic systems; threshold crossing; falsifiability; theoretical modeling.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-08
DOI
https://doi.org/10.5281/zenodo.24061998
Primary Topic
Memory Processes and Influences
Type
preprint
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preprint

The Meta-Representational Preemption Principle (MRPP) A Conditional Framework for Self-Referential Priority Shifts in Retrieval and Selection Systems

Shamiul Hoque Shan
1 links
Zenodo (CERN European Organization for Nuclear Research)
Memory Processes and Influences
preprint

The Meta-Representational Preemption Principle (MRPP) A Conditional Framework for Self-Referential Priority Shifts in Retrieval and Selection Systems

Shamiul Hoque Shan
preprint en

Abstract

This paper proposes the Meta-Representational Preemption Principle (MRPP), a conditional theoretical framework for examining situations in which a representation of a selection process may become accessible before the target items that the process was intended to select. The framework originates from a primary case in which an individual establishes a rule for which of two or more thoughts should be recalled first. During a subsequent recall attempt, the individual may instead become aware of the competition rule, the prior commitment, or the process of determining which thought will appear first. This process-related representation was not included in the original candidate set, yet it may become the first consciously available content.The paper formalizes this case as the Self-Referential Recall-Preemption Case (SRRPC). It distinguishes candidate-set membership, activation, conscious availability, reported first occurrence, and subsequent behavioral influence. The proposed mathematical architecture includes candidate-set notation, threshold-crossing times, a conditional preemption indicator, candidate activation dynamics, a probabilistic first-choice model, and an information-theoretic description of uncertainty. It then examines possible recursive structures, boundary conditions, cross-domain analogies, competing explanations, and falsifiable empirical predictions.The framework is intended to be medium-independent only in a conditional structural sense: its proposed mechanism may be investigated in any system where a defined candidate set, a representation of the selection process, and a shared priority or access mechanism can be independently identified. Such generality is a research hypothesis, not an established universal law. The equations are candidate formal models rather than validated descriptions of human neurobiology. No empirical results are claimed. The principal objective is to transform the original conceptual observation into an operationally defined, mathematically explicit, and potentially falsifiable research program.Keywords: metacognition; self-reference; memory retrieval: priority competition; candidate-set divergence; attentional selection; dynamic systems; threshold crossing; falsifiability; theoretical modeling.

Zenodo (CERN European Organization for Nuclear Research)
Memory Processes and Influences
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