Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

Abstract

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.

Ten Meta Science Insights to Deal With the Credibility Crisis in the Social Sciences

“…Meta research projects of the 'Many analysts, one dataset' type, in which many researchers are testing the same hypothesis with the same dataset, demonstrate that researcher degrees of freedom easily lead to entirely different conclusions. In a recent study relying on international survey data, researchers were asked to estimate the association between immigration and public support for government provision of welfare (Breznau et al, 2022). 25% of estimates were significantly negative, 17% were positive, and 58% had a confidence interval including 0.…”

A universe of uncertainty hiding in plain sight

“… Variation in reported results from Brady and Finnigan ( 4 ) which Breznau et al. ( 1 ) replicate. Point estimates for 3 variables: percent foreign born, net migration, and change in percent foreign born.…”

“…In an impressive effort, Breznau et al. ( 1 ) (henceforth, BRW) report a many-analyst collaboration where multiple teams were involved in analyzing the same data and hypothesis: that immigration undermines public support for social policy. Like other such studies ( 2 , 3 ), the results show considerable variation and are sure to ignite debate.…”

“…Despite this variation, the study successfully replicates a published null finding. BRW chose their research question because it is “influential, long standing, and typical” ( 1 ). But according to the earlier study that BRW replicate ( 4 ), results “mostly fail to support” the hypothesis.…”

“…1 ). It is therefore contestable that variation “remains hidden when considering a single study in isolation” ( 1 ).…”