Scientific truth viewed as | Singular (ie, there is one set of facts which will be found by using the correct scientific methods) | Multiple (ie, there are many legitimate scientific perspectives on a problem, so multiple methods may be needed) |
Goal of research | Establishing the truth, which is seen as universal and generalisable | Exploring tensions; generating insights; revealing multiple perspectives |
Assumed model of causality | Linear, cause-and-effect; a fixed input has a fixed effect size | Emergent: many interacting influences, but none has a fixed ‘effect size’ |
Typical format of research question | ‘What is the effect size of the intervention on the predefined outcome, and is it statistically significant?’ | ‘What combination of influences has generated this phenomenon? What does the intervention of interest contribute? What happens to the system and its actors if we intervene in a particular way? What are the unintended consequences elsewhere in the system?’ |
Good research defined in terms of | Methodological rigour, standardisation, precision | Strong theory, flexible methods, pragmatic adaptation to changing circumstances |
Most valued study designs | Randomised controlled trials, meta-analyses | No single design is ‘most valued’. A combination of designs—for example, multilevel intervention studies, naturalistic case studies, modelling studies—is preferred |
Purpose of theorising | Disjunctive (simplification and abstraction) | Conjunctive (drawing together different parts of a complex problem) |
Approach to data collection | Continue collecting data until the dataset is complete and agreed | Data will never be complete; decisions must sometimes be made on the basis of incomplete or contested data |
Analytic focus | Dualisms: comparing A with B; finding the influence of X on Y | Dualities: inter-relationships and tensions between A, B, C and other emergent phenomena |