Is the left-right scale a valid measure of ideology? Individual-level variation in associations with "left" and "right" and left-right self-placement

This article focuses on the measurement of trust. First, we start with a brief conceptualization of trust, contrasting it with the concept of generalized trust. Second, we survey developments in trust measurement since the 1960s. Third, we summarize and try to systematize a number of measurement debates that have taken place. Fourth, we outline how trust measurement may develop in the future, discuss how differently formulated survey questions may abate some of the debates within the field, and present empirical data that follow some of these directions. Essentially we argue that trust—as opposed to generalized trust—should be measured through reliance on a set of more specific questions that measure expectations across a series of different situations.

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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.