Deep Collaboration Methodology (DCM): Architecture Design and String Encoding System: A Logical Diagnostic Tool for Micro-Field Surveys
This report details the theoretical framework and data encoding system of the Deep Collaboration Methodology (DCM). DCM aims to capture the black-box cognition and ethical boundaries of humans collaborating with artificial intelligence through micro-field investigations. This study designed a funnel-shaped questioning strategy to guide respondents from instrumental use to deeper ethical debate. The core contribution lies in the development of a string-based recording system that uses "cognitive dissonance flags (!)" and "responsibility shift flags (?)" to instantly detect logical breaks in respondents. This framework provides independent researchers with an empirical research paradigm possessing forensic-level integrity in non-institutional settings.
Authors
- Chen-Chieh Fan
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-01-07
- DOI
- https://doi.org/10.5281/zenodo.18170808
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00