THE QUALIFIED DETERMINISM PRINCIPLE: A Framework for Information-Conditioned Causality Across Scales
Abstract
The Qualified Determinism Principle, which asserts that predictability is not an absolute trait of a physical system but rather depends on the **resolution** and the specific **question** being asked. It establishes a measurable degree of determinism using **Shannon entropy** and demonstrates that finer observational scales generally feature shorter **predictability horizons**. This framework explains how complex phenomena like **turbulence**, **low-dimensional chaos**, and **quantum decoherence** can yield unpredictable individual outcomes while maintaining stable, deterministic statistical distributions. Additionally, the literature examines a physical **substrate floor** where thermal noise ultimately overwhelms organized fluid motion, thereby separating the practical limits of **forecasting** from the theoretical continuity of underlying mathematical equations.
Related
- EAS / Scalar Fields: Quantum Gravity: Relational Scale, Conditioned-Region Source Organization, and Qualified Correspondence to General Relativity
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- Information-Geometric Grammar Principle: A Statistical-Geometric Framework for Adaptive Systems
- The Existence Conjecture of an Exact Universal Predictor: Causal Determinism, Global Evolution Maps, and Complete Information Structures
- The Criterion-Conditioned Manifestation Principle (CCMP)
BibTeX
@misc{kruse2026qualified,
title = {{THE QUALIFIED DETERMINISM PRINCIPLE: A Framework for Information-Conditioned Causality Across Scales}},
author = {Christopher Grant Kruse},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23659404},
url = {https://zenodo.org/records/23659404},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - THE QUALIFIED DETERMINISM PRINCIPLE: A Framework for Information-Conditioned Causality Across Scales
AU - Christopher Grant Kruse
PY - 2026
DA - 2026/10/26
PB - Zenodo
DO - 10.5281/zenodo.23659404
UR - https://zenodo.org/records/23659404
AB - The Qualified Determinism Principle, which asserts that predictability is not an absolute trait of a physical system but rather depends on the **resolution** and the specific **question** being asked. It establishes a measurable degree of determinism using **Shannon entropy** and demonstrates that finer observational scales generally feature shorter **predictability horizons**. This framework explains how complex phenomena like **turbulence**, **low-dimensional chaos**, and **quantum decoherence** can yield unpredictable individual outcomes while maintaining stable, deterministic statistical distributions. Additionally, the literature examines a physical **substrate floor** where thermal noise ultimately overwhelms organized fluid motion, thereby separating the practical limits of **forecasting** from the theoretical continuity of underlying mathematical equations.
ER -