The Listening Coefficient Reproducibility Package
Year: 2026
Type: software
Abstract: Reference implementation and reproducibility materials for “The Listening Coefficient: A Diagnostic Framework for Feedback Integrity” (Systems Research and Behavioral Science, accepted 2026). A single self-contained Python script regenerates, from fixed seeds, the controlled synthetic adaptive-system log, component and aggregate estimates, 800-replicate moving-block bootstrap confidence intervals, aggregation-rule comparison, timeliness � sensitivity analysis, bootstrap component correlations, leave-one-component-out profiles, and all three figures reported in the article. No real-world or personal data are included; the demonstration data are entirely synthetic. The archive contains the reference Python implementation, generated CSV and JSON outputs, manuscript figures, README, requirements file, citation metadata, and licences. Code is released under the MIT licence. Synthetic data files and figures are released under CC BY 4.0. The manuscript’s Data and Code Availability section says the package regenerates the synthetic log, component estimates, bootstrap intervals, aggregation comparison, sensitivity curve, component correlations, leave-one-component-out profiles, and figures, with explicit seeds and estimator definitions. The script header matches that scope and states that no real-world data are required.
Author: Bryan, Daniel
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7203567936