Operationalizing Narrative Entropy (Sn): A Two-Scene Registered Pilot Report and Pre-Validation Protocol
Abstract
Narrative Entropy (Sn) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes processing load on a reader. To date the construct has been defined theoretically but not operationalized against real texts. This report documents the first such operationalization (the v2.0 pilot): two narrative scenes — the opening restaurant scene of Quentin Tarantino's Reservoir Dogs screenplay and the opening interior-monologue block of Raymond Carver's short story Cathedral — were coded manually by a single rater and scored with the candidate formula Sn = If × Cb × t. The result was contrary to intuitive expectation. The single-voice monologue block (Sn = 30.0) scored higher than the nine-character rapid-dialogue scene (Sn = 18.8). We treat this divergence not as a result to be explained away but as the central finding of the pilot, and we deliberately refuse post-hoc adjustment of the formula. We present three competing interpretations of the divergence — formula incompleteness, genuine high-load prose, and measurement error — and we specify, in advance of data collection, the design that would discriminate among them. This document functions simultaneously as a pilot report (n = 2) and as a pre-registration of the next-stage protocol. It explicitly does not claim that Sn has been validated. Keywords: narrative entropy, operationalization, pilot study, pre-registration, falsifiability, Bulut Doctrine, computational narratology, processing load
Fields of Study & Subjects
Narrative Theory and Analysis
Artificial Intelligence in Games
Authorship Attribution and Profiling
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 24 May 2026
- Language
- ENC