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Causality, within sociology, has been the subject of epistemological debates, particularly concerning the external validity of research findings; one factor driving the tenuous nature of causation within social research is the wide variety of potential "causes" that can be attributed to a particular phenomena.
The cause involves access to resources that can assist in avoiding health risks or to minimize the sequelae of disease once it occurs. "The association between a fundamental cause and health is reproduced over time via the replacement of intervening mechanisms" [2] By these criteria, SES is a fundamental cause for healthcare disparities.
E. O. Wilson defined sociobiology as "the extension of population biology and evolutionary theory to social organization". [6]Sociobiology is based on the premise that some behaviors (social and individual) are at least partly inherited and can be affected by natural selection. [7]
A sociological theory is a supposition that intends to consider, analyze, and/or explain objects of social reality from a sociological perspective, [1]: 14 drawing connections between individual concepts in order to organize and substantiate sociological knowledge.
A proximate cause is an event which is closest to, or immediately responsible for causing, some observed result. This exists in contrast to a higher-level ultimate cause (or distal cause) which is usually thought of as the "real" reason something occurred. The concept is used in many fields of research and analysis, including data science and ...
Causality is an influence by which one event, process, state, or object (a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. [1]
The term social mechanisms and mechanism-based explanations of social phenomena originate from the philosophy of science.. The core thinking behind the mechanism approach has been expressed as follows by Elster (1989: 3-4): “To explain an event is to give an account of why it happened.
Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...