metascience
Definition
Metascience is the systematic study of scientific practices, methodological choices, and the conditions under which research findings replicate or diverge across studies. Applied to misinformation research, it encompasses the examination of how analytical decisions, such as the operationalization of political ideology, the selection of news stimuli, and the choice of statistical approach, produce contradictory conclusions even when researchers use pre-registered designs and shared datasets. A re-analysis of 12 studies totaling 6,790 participants demonstrated that opposite conclusions about conscientiousness as a moderator of ideology-based fake news sharing could be traced directly to these kinds of decisions rather than to genuine differences in the underlying phenomenon.
Sources: Lawson & Kakkar (2024)
Related Terms
- misinformation (1 shared article)
- interventions (1 shared article)
- fake news (1 shared article)
- conscientiousness (1 shared article)
Applications
Metascience and Misinformation Research
Metascience provides the tools for identifying why misinformation studies yield conflicting results, including disagreements over whether accuracy prompts reduce sharing equally across the political spectrum and whether conscientiousness moderates the relationship between ideology and fake news sharing. A specification curve analysis across 35 analytical specifications found that 21 models produced statistically significant interaction effects, illustrating how the choice of specification alone determines whether an effect appears or disappears. The framework proposed from this work aims to accelerate convergence by making researchers' methodological decisions an explicit object of scrutiny.
Sources: Lawson & Kakkar (2024)
Metascience and Methodological Choices
The selection of an ideology measure is consequential: most measures used in one set of studies were not positively correlated with fake news sharing overall, which precluded observing the attenuation moderation that a different operationalization readily revealed. Heterogeneity statistics from the re-analysis, with I² values of 99.1% and 95.8% across two sets of studies, confirm that context-specific methodological factors account for the vast majority of variance in observed effect sizes.
Sources: Lawson & Kakkar (2024)
