Condition OS: A Thinking Framework Based on Conditions, Probabilities, and Intervention

Condition OS is a general thinking framework designed to shift the starting point of analysis from observed outcomes to the conditions that make those outcomes possible and affect their probabilities. Rather than treating success, failure, behavior, or rare events as self-explanatory, the framework encourages users to identify relevant conditions, map their interactions, estimate their influence, intervene on modifiable conditions, and update the model as new information becomes available. Condition OS is not presented as a new scientific theory. It integrates and simplifies ideas related to probabilistic causation, causal models, configurational causation, optimization, sequential decision-making, and systems thinking into a practical reasoning process intended to be usable across disciplines and everyday decision-making. The central process is: Observe → Decompose → Structure → Estimate → Intervene → Update. This record contains the English version of the document. AI-assisted writing and document preparation are transparently disclosed within the paper.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-14
DOI
https://doi.org/10.5281/zenodo.22740203
Primary Topic
Bayesian Modeling and Causal Inference
Type
preprint
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Condition OS: A Thinking Framework Based on Conditions, Probabilities, and Intervention

Naori Kurata
Zenodo (CERN European Organization for Nuclear Research)
Bayesian Modeling and Causal Inference
preprint

Condition OS: A Thinking Framework Based on Conditions, Probabilities, and Intervention

Naori Kurata
preprint en

Abstract

Condition OS is a general thinking framework designed to shift the starting point of analysis from observed outcomes to the conditions that make those outcomes possible and affect their probabilities. Rather than treating success, failure, behavior, or rare events as self-explanatory, the framework encourages users to identify relevant conditions, map their interactions, estimate their influence, intervene on modifiable conditions, and update the model as new information becomes available. Condition OS is not presented as a new scientific theory. It integrates and simplifies ideas related to probabilistic causation, causal models, configurational causation, optimization, sequential decision-making, and systems thinking into a practical reasoning process intended to be usable across disciplines and everyday decision-making. The central process is: Observe → Decompose → Structure → Estimate → Intervene → Update. This record contains the English version of the document. AI-assisted writing and document preparation are transparently disclosed within the paper.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Bayesian Modeling and Causal Inference
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Condition OS: A Thinking Framework Based on Conditions, Probabilities, and Intervention — Naori Kurata · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS