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The Hidden Decline of Trust in Science

Author

Listed:
  • Bulbulia, Joseph

    (Victoria University)

  • Kerr, John R
  • Houkamau, Carla
  • Osborne, Danny
  • Wilson, Marc
  • Yogeeswaran, Kumar
  • Sibley, Chris G

    (University of Auckland)

Abstract

Surveys of trust in science are conducted by scientists, creating a structural selection problem: those who distrust science are less likely to participate. In cross-sectional designs this bias is invisible; in panel studies it appears as differential attrition that inflates apparent trust over time. Using five waves (2019–2024) from a national probability panel in New Zealand (N = 42,681) and multiple imputation to correct attrition bias, we find that apparent gains in the social value of science vanish after correction and that confidence in scientists, after an initial pandemic-era rise, falls to or below baseline by 2024. Simulation analyses indicate that correction methods recover trajectories under standard missing-data assumptions. Categorical estimates reveal hidden erosion of high confidence in scientists and growth in low trust that uncorrected data obscure.

Suggested Citation

  • Bulbulia, Joseph & Kerr, John R & Houkamau, Carla & Osborne, Danny & Wilson, Marc & Yogeeswaran, Kumar & Sibley, Chris G, 2026. "The Hidden Decline of Trust in Science," SocArXiv tynr4_v1, Center for Open Science.
    • Handle: RePEc:osf:socarx:tynr4_v1
    DOI: 10.31219/osf.io/tynr4_v1
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    References listed on IDEAS

    as
    1. Honaker, James & King, Gary & Blackwell, Matthew, 2011. "Amelia II: A Program for Missing Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i07).
    2. James Honaker & Gary King, 2010. "What to Do about Missing Values in Time‐Series Cross‐Section Data," American Journal of Political Science, John Wiley & Sons, vol. 54(2), pages 561-581, April.
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