MétaCan
Menu
Back to cohort
Record W7116101108 · doi:10.5281/zenodo.17973989

Obligation Closure Constraint (OCC): The First Principle

2025· preprint· en· W7116101108 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typepreprint
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsStock (firearms)Constraint (computer-aided design)Robustness (evolution)Empirical researchIdentifierEmpirical evidenceSoftwareEquity (law)

Abstract

fetched live from OpenAlex

DESCRIPTION OCC is a falsifiable constraint on completion rates in systems where humans must make defensible, contestable decisions. The core claim: Durable completion rate cannot exceed verification capacity divided by verification effort per item. When more decisions require checking than capacity allows, the gap must manifest as observable outputs—backlog growth, rework, displacement to other parties, declining quality standards, or persistent degradation after overload. Modern large-scale coordination increases complexity, change rate, and required standards faster than human decision-making capacity scales. This creates a structural mismatch that worsens over time independent of institutional intent or effort. The constraint applies to any consequence-bearing boundary requiring accountable human judgment: courts, healthcare administration, permitting, insurance adjudication, safety certification, and high-stakes review processes in software and operations. This document provides the theoretical foundation for OCC. Companion records provide formal specification, measurement protocol, and empirical deployments. Empirical Deployments (Tier-1): Three case studies have been executed using the OCC framework, demonstrating its ability to discriminate between sustainable and overloaded regimes: Washington, DC FOIA Request Processing (2020–2025) — Regime diagnosis: Busy but stuck. DCR ≈ 0.88, stock grew from ~1 to >3,360 cases. DOI: 10.5281/zenodo.18073749 Philadelphia L&I Appeals Processing (2010–2018) — Regime diagnosis: Busy but stuck. DCR ≈ 0.92, stock grew from 202 to 1,983 cases. DOI: 10.5281/zenodo.18076572 City of Vancouver Building Permits (2018–2025) — Regime diagnosis: Sustainable. DCR ≈ 1.04, stock declined from 494 to zero. DOI: 10.5281/zenodo.18077993 These deployments confirm the framework's core discriminative capacity: identical methodology applied to different systems produces divergent regime classifications that match observed stock dynamics. Related Identifiers Add all three as "IsSupplementedBy": https://doi.org/10.5281/zenodo.18073749 https://doi.org/10.5281/zenodo.18076572 https://doi.org/10.5281/zenodo.18077993

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0040.012
Scholarly communication0.0080.016
Open science0.0040.006
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0200.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.272
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicSystems Engineering Methodologies and ApplicationsFrench-language works237,207