Beyond the Cortical Label: A Physical Parameter Framework for Narrative Engineering and Autonomic Reader Response.

Read full text
Authors: Levent BULUT
Cited by: 2

Abstract

Current Large Language Models (LLMs) consistently fail to produce genuine emotional resonance in human readers, primarily due to a reliance on "high road" cortical interpretation through explicit emotion labels (e.g., "she felt sad"). This paper introduces the Objective Projection methodology, a biophysical approach to narrative engineering that bypasses cultural and linguistic filters to activate "low road" autonomic responses. By utilizing six specific physical variables—Luminous Decay, Thermal Gradient, Acoustic Impedance, Kinetic Momentum, Atmospheric Pressure, and Spatial Geometry—narrative constructs can be engineered to trigger predictable physiological changes (heart rate, breathing, muscle tone) before conscious interpretation occurs. The paper outlines: The transition from T.S. Eliot’s "Objective Correlative" to the more rigorous Objective Projection. The Six Constitutional Rules of the Bulut Doctrine (including Emotion Embargo and Simile Prohibition). The technical derivation of Narrative Entropy ($S_n$) and Narrative Gravity ($N_g$). The structural overview of the 500-scene SFT (Supervised Fine-Tuning) corpus and the OPCT v2.0 experimental protocol. This methodology treats the reader’s biology as a Universal Biological Interface (UBI), proposing a transition from literature-as-art to literature-as-physics. The framework aims to standardize the production of high-resonance AI prose and provide a measurable basis for neuroaesthetic research.Official: leventbulut.com Keywords: Objective Projection, Bulut Doctrine, Narrative Physics, Neuroaesthetics, AI Ethics, Narrative Entropy, Biophysical Output, SFT Dataset, Digital Humanities.

Fields of Study & Subjects

Media Influence and Health Narrative Theory and Analysis Aesthetic Perception and Analysis

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 May 2026
Language
ENC