Substrates Encode Experience, Not Information: An Encoding-through-Loading Framework with Cross-Substrate Tests in Language Models

Paper 4B in the Friction Theory paper-series — version 3. An eight-experiment empirical paper on language-model substrates that proposes and tests an encoding-through-loading framework, situating it against Cognitive Load Theory (Sweller) and within the recent Multiple Moderated Mediations (Triple-M) framework for prior knowledge × learning (Simonsmeier & Schneider 2025). Abstract. We propose that substrates — biological and artificial — encode the processing-friction (the friction-signature generated by operating on input-friction), not the information they receive. Inputs that do not open a race in the substrate leave no trace; inputs that open a race the substrate must resolve leave a trace structured by the resolution. The triggers of such races — reactance, pseudo-complexity attribution, capacity-overload, expectation-violation, personal relevance — are sourced from human cognitive psychology; this paper tests their LLM-side analogues and presents evidence consistent with cross-substrate operation. The persistence layer differs: human substrates accumulate cross-session encoding-traces; language models without persistent memory architectures pay friction within a generation but do not propagate it. The mechanism reduces, via predictive-coding, to unreducible prediction-error: random noise habituates to non-signal and costs nothing regardless of volume; ambiguous-but-plausible content cannot be categorised and costs continuously regardless of token-count. Eight predictions tested on multiple LLM substrates: (1) substrate-graded U-curve in expertise-reversal across model size; (2) per-token CR peaks at 1-shot strategy-crossover; (3) elaborated demonstrations reduce friction relative to minimal demonstrations; (4) format-violation produces a 22pp accuracy collapse with measurable CR rise; (5) within-session repetition produces no encoding gain; (6) random-nonsense fillers cost only 13pp across a 1600× volume increase; (7) sweet-spot capacity-graded peaks collapse to overload-floor under pressure; (8) exploratory placement-signature re-analysis identifies trigger-specific patterns. Theoretical positioning. The race-account is positioned within the Triple-M framework as a substrate-level operational specification beneath four of its sixteen mediators (interference, strategy change, skill automatization, transfer). §7.4 elaborates the framework's didactic implications and connects the substrate-mechanism to existing traditions in pragmatic-uptake (Grice, Sperber & Wilson, Clark & Brennan, Kintsch) and now to social-learning / social-influence (Bandura, Cialdini, Deutsch & Gerard, Henrich & McElreath). The framework recovers Dewey's learning-by-doing, mirror-friction, Shackleton-Jones's Emotional Context Theory, Transfer-Appropriate Processing, the peak-end heuristic, and the Yerkes-Dodson curve as observation-windows on one substrate-level process. Companion papers in the Friction Theory series: Paper 0 (Behavioural Friction Theory): 10.5281/zenodo.19462499 Paper 1 (Friction Theory substrate): 10.5281/zenodo.20012654 Paper 2 (Capacity scaling): 10.5281/zenodo.20013491 Paper 2B (ICL/FT substrate mechanism): 10.5281/zenodo.20145218 Paper 3 (Friction-guided inference): 10.5281/zenodo.20014121 Paper 10 (Race-architecture across substrates): 10.5281/zenodo.20014567 Paper 13 (Operational Friction Theory): 10.5281/zenodo.20059876 Target venue: Cognitive Science (Wiley) for journal submission after preprint feedback. What is new in v3 (relative to v2): New section §7.4e "Observation-channel extension: substrate-mechanism beneath informational social influence" (~430 words). The §7.4d receiver-side mirror-friction mechanism generalises from communicated content (verbal artefact) to observed action (behavioural artefact). The framework hypothesises that the observer's race-state on the situation-class updates toward the observed agent's apparent friction-resolution, lowering future processing-friction without first-hand learning cost. Framed explicitly as a substrate-mechanistic specification beneath existing informational social influence (Deutsch & Gerard 1955) and Bayesian social-learning (Henrich & McElreath 2003) — not as a new behavioural prediction. Candidate action-channel proxies anchored in motor-control / decision-kinematics literature (jerk-minimisation per Flash & Hogan 1985; changes-of-mind per Resulaj/Kiani/Wolpert 2009; motor variability per Wolpert & Ghahramani 2000); social-correlation caveat per Lorenz/Rauhut/Schweitzer 2011 PNAS. Reactance boundary condition reframed as attenuation via persuasion-knowledge (Friestad & Wright 1994), not sign-reversal. Triple-M section renumbered from §7.4e to §7.4f. Bibliography expanded from 84 to 97 entries: 13 new cites bridging social-learning, persuasion-knowledge, motor-control, and decision-kinematics literatures. The v2 §7.4d receiver-side mirror-friction (communication as pragmatic uptake on top of channel-fidelity) is unchanged in v3. The v1 empirical contribution (eight experiments on Qwen2.5/Llama-3.3/Qwen3-235B/DeepSeek-V3 with the chemistry composition task Y = N × X) is also unchanged.