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Download as PDF; Printable version; ... Causality is an influence by which one event, ... Karma is the causality principle focusing on 1) causes, 2) actions, 3 ...
Pluralized causal principle - there are pluralized versions of universal causation, that allow exceptions to the principle. Robert K. Meyer's causal chain principle, [15] uses set theory axioms, assumes that something must cause itself in set of causes and so universal causation doesn't exclude self-causation. Against infinite regress.
Causality can be defined macroscopically, at the level of human observers, or microscopically, for fundamental events at the atomic level. The strong causality principle forbids information transfer faster than the speed of light; the weak causality principle operates at the microscopic level and need not lead to information transfer.
Idappaccayatā (Pali, also idappaccayata; Sanskrit: idaṃpratyayatā) is a Buddhist term that is translated as "specific conditionality" or "this/that conditionality". It refers to the principle of causality: that all things arise and exist due to certain causes (or conditions), and cease once these causes (or conditions) are removed.
The Bradford Hill criteria, otherwise known as Hill's criteria for causation, are a group of nine principles that can be useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an observed effect and have been widely used in public health research.
Causal reasoning is the process of identifying causality: the relationship between a cause and its effect.The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one.
In the Scholasticism, the efficient causality [35] was governed by two principles: omne agens agit simile sibi [36] [37] [38] (every agent produces something similar to itself): stated frequently in the writings of St. Thomas Aquinas, the principle establishes a relationship of similarity and analogy between cause and effect;
Causality: Models, Reasoning, and Inference (2000; [1] updated 2009 [2]) is a book by Judea Pearl. [3] It is an exposition and analysis of causality. [4] [5] It is considered to have been instrumental in laying the foundations of the modern debate on causal inference in several fields including statistics, computer science and epidemiology. [6]