Multidimensional concepts are non-compensatory when higher values on one component cannot offset lower values on another. Thinking of the components of a multidimensional phenomenon as non-compensatory rather than substitutable can have wide-ranging implications, both conceptually and empirically. To demonstrate this point, we focus on populist attitudes that feature prominently in contemporary debates about liberal democracy. Given similar established public opinion constructs, the conceptual value of populist attitudes hinges on its unique specification as an attitudinal syndrome, which is characterized by the concurrent presence of its non-compensatory concept subdimensions. Yet this concept attribute is rarely considered in existing empirical research. We propose operationalization strategies that seek to take the distinct properties of non-compensatory multidimensional concepts seriously. Evidence on five populism scales in 12 countries reveals the presence and consequences of measurement-concept inconsistencies. Importantly, in some cases, using conceptually sound operationalization strategies upsets previous findings on the substantive role of populist attitudes.

Democracies without democrats are not sustainable. Yet, recent studies have argued that Western citizens are turning their backs on the system of self-governance, thereby eroding the societal foundations of consolidated democracies. This study contributes to discussions about citizen support of democracy by (1) analyzing new cross-national survey data in 18 European countries that facilitate assessments of the temporal and geographical generalizability of previous findings, (2) disentangling age, cohort and period effects, thereby aligning the analytical methods with the theoretical arguments and (3) transparently reporting all evidence derived from pre-registered analyses to avoid cherry-picked findings. The findings show that citizens of consolidated democracies continue to endorse self-governance. Yet in some (but not all) countries, there is evidence of a growing number of ‘democrats in name only’, particularly among the young generation. These findings suggest a second phase in research on democratic fatigue that broadens the analytical scope for the multi-faceted nature of democratic support.

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.