What data counts in policymaking and programming evaluation - Relevant data sources for triangulation according to main epistemologies and philosophies within social science.

Policy analysis and program evaluation quality guides how impact is measured, revisions are made, and allocations of resources is deployed. As interdisciplinary research grows in contemporary policy science, the importance of defining truth can be contentious among different social scientists. This research traces the history of triangulation to its contemporary version within the social sciences. The study examines the philosophical evolution influencing the environment in which triangulation develops including: consilience and the comparative linguistic structure of the traditions of thought; and the historical development of methods and emergence of triangulation in research. It also offers contrasting interpretations of triangulation within the various epistemologies and philosophies of science that have arisen in recent movements within social science. As research strives to address novel 21st century issues including big data, pandemics, misinformation, and globalization, there is a need for rigorous social science and policy-based research to be aware of different interpretations of empirical data and valid research methods across disciplines, examine new and old phenomena using multi-method approaches, and validate data informing policy through methods of triangulation.