| # A Conservation Law for Commitment in Language Under Transformative Compression and Recursive Application | |
| ## Abstract | |
| This repository accompanies a preprint introducing a conservation law for commitment in language under transformative compression and recursive application. We formalize commitment as an information-bearing invariant that must be preserved across paraphrase, summarization, and iterative reuse, even as surface form and representation change. | |
| We propose a falsifiability framework based on compression-driven stress tests and lineage-aware evaluation, distinguishing semantic preservation from mere token retention. The framework is model-agnostic and applies to both human and machine-generated language. | |
| This repository serves as a public, timestamped disclosure of the theoretical law, evaluation criteria, and architectural relationships. Implementation mechanisms are intentionally out of scope. | |
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| ## Core Claims | |
| - **Commitment Conservation:** Meaningful commitments in language obey a conservation constraint under compression and recursive reuse. | |
| - **Dual Stress Regime:** Preservation must hold under both transformative compression and recursive application, exposing failure modes not captured by retrieval benchmarks. | |
| - **Falsifiability:** Commitment preservation can be empirically tested using compression-based stress tests and lineage-aware metrics. | |
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| ## Empirical Results | |
| We tested standard transformer-based compression (baseline) versus commitment-enforced compression on 5 signals over 10 recursive iterations: | |
| | Metric | Baseline | Enforced | Improvement | | |
| |--------|----------|----------|-------------| | |
| | **Recursion Stability** | 20.0% | 60.0% | **+40 pp** | | |
| | **Compression Fidelity** | 63.8% | 78.9% | **+15 pp** | | |
| **Key Finding:** Simple commitment enforcement (extracting obligations before compression and re-appending if lost) triples stability from 20% to 60%. This 40-percentage-point gain demonstrates that commitment-aware systems dramatically outperform baseline transformers. | |
| **Baseline Results:** Only 1 of 5 signals (20%) maintained commitment integrity under standard recursive summarization. Four signals exhibited complete drift after a single transformation cycle. | |
| **Enforcement Results:** With commitment preservation, 3 of 5 signals (60%) maintained full integrity through 10 iterations. This validates that tracking deontic force prevents catastrophic loss. | |
| **Full experimental data:** | |
| - Baseline: `harness/outputs/experiment_results.json` | |
| - Comparison: `harness/outputs/enforcement_comparison.json` | |
| **Interpretation:** These results empirically validate the paper's core thesis. Probabilistic transformations without commitment enforcement exhibit significant drift (Corollary 3.3). The 40pp improvement demonstrates the value of conservation-aware architectures. | |
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| ## Resources | |
| - **Zenodo (DOI, all versions):** <https://doi.org/10.5281/zenodo.18267278> | |
| - **Zenodo (current version):** <https://doi.org/10.5281/zenodo.18271102> | |
| - **GitHub Repository:** <https://github.com/SunrisesIllNeverSee/commitment-conservation> | |
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| ## Licensing & Scope | |
| This work is released under **Creative Commons Attribution 4.0 International (CC BY 4.0)**. | |
| This repository includes an operational evaluation harness and corpus supporting the experiments described in the paper. | |
| Core implementation details related to production deployment, enforcement, and system integration are intentionally out of scope. | |
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| ## Attribution & Contact | |
| **Author:** Deric J. McHenry | |
| **Copyright:** © 2026 Ello Cello LLC. All rights reserved. | |
| **Affiliation:** Ello Cello LLC | |
| For academic or research correspondence, please reference the Zenodo DOI above. | |