Deviant scrutiny methodology: Applications in the war against inequality

Evandro Bocatto, PhD

We argue that research methodologies in management sciences often neglect the negative impact businesses may
have on societies. To mitigate this problem, we suggest a deliberate integration of adjacent effects in the data
collection of any topics under study. We call this approach to data sampling and collection, deviant scrutiny
methodology. Deviant scrutiny can be defined as research methodology that emphasizes an integrative data
collection that actively incorporates a variety of externalities into the dataset. The methodology shares three
characteristics with Thomas Kuhn’s view: 1. an identified conception, metaphysics and values, viz., the approach
includes externalities (i.e., sense of purpose); 2. an historical consideration focusing on emerging topics, or
social facts, that affects society and organizations (i.e., sense of context); and, 3. the compulsory, by protocol,
integration of evidences that challenge taken for granted assumptions and theories, and confronts the biases
affecting scientific communities-of-practice (i.e., sense of awareness).