Boundary-Conditioned Agency and Distributed Selector Persistence: A Formal Framework for Cross-Channel Mismatch, Transformation Survival, and Downstream Selection

This preprint presents a formal methods framework for investigating whether recurrent mismatch between coupled communication channels can function as a distributed selection surface that alters downstream interpretation, weighting, and action. The paper introduces the M0–M4 persistence ladder, a pattern identity rule with five invariant dimensions, a seven-category functional role taxonomy, a three-class transformation hierarchy, a three-layer corpus structure with lexical-content controls, and a calibration protocol with quantified inter-rater agreement thresholds.

The framework is designed to distinguish informative mismatch from persistent mismatch, distributed selector persistence, and boundary-conditioned agency. It is fully falsifiable at each level independently and is intended to support independent replication and critique prior to empirical data collection.

Empirical validation is in preparation. Planned follow-on papers include coder calibration results, a 20-event M3 pilot, and M4 assessment only if M3 is confirmed.

Related planned works include a coder calibration paper on inter-rater agreement and invariant scoring, a 20-event pilot study testing distributed selector persistence (M3) across controlled transformations and lexical-content controls, and a later M4 assessment only if M3 is confirmed.

Together, these planned papers form a staged empirical roadmap from methods specification to downstream action-level testing.

Keywords:

boundary-conditioned agency

distributed selector persistence

cross-channel mismatch

multimodal communication

pattern identity

functional role taxonomy

transformation survival

lexical-content control

predictive processing

gesture-speech mismatch

prosody

downstream selection

inter-rater calibration

multimodal AI

voice-text divergence