Measurement of Evidences

Operationalization

Operationalization is the process of defining an abstract concept in terms of specific observable or measurable indicators so that claims involving the concept can be examined using evidence.

Quantitative Evidence

Quantitative evidence is numerical information used to evaluate a claim, pattern, or explanation. Numbers can provide strong evidence, but what they support depends on how the relevant variables were defined, measured, and interpreted.

Disaggregation

Disaggregation is the process of breaking aggregated data into relevant subgroups, categories, locations, time periods, or other components in order to reveal patterns that may be hidden by an overall total or average.

Fact–Value Distinction

The fact–value distinction separates descriptive claims about what is or was the case from normative claims about what ought to be, what is good or bad, or what should be done. Factual evidence alone does not automatically establish a normative conclusion.

Normative Premise

A normative premise is a value-based assumption or principle that helps connect descriptive facts to a conclusion about what ought to be valued, judged, or done.

Selection Effect

Occurs when the process determining which cases, observations, or individuals enter a group or dataset influences the pattern that is observed. Differences between selected groups may therefore reflect how the cases were selected rather than solely the factor being investigated