SCORE

Tags:replicationmetascience paperrandom sampleHover over the tag text for details.
Domainsocial & behavioural sciences
Datareplications of 163 claims + 1.9k claims from papers
Note

To download only this data file: SCORE_all_claims.rds (232 KB); SCORE_replications.rds (47 KB)

To download all BEAR datasets, click here.

Description

Reference: Tyner et al. (2026).

Research question: investigating the replicability of published claims in the social and behavioural sciences.

Data availability: the SCORE replication package is available at https://osf.io/g5sny/. The package includes replication data as well as reviews of claims made in included papers.

Data description and source: BEAR includes two SCORE outputs. The replications source dataset has 548 rows: 274 original claims and 274 matched replications. After BEAR processing and filtering, 267 matched replication rows are retained. The “all claims” source dataset has 3,066 claim-level rows from the set of replicated papers (but no replications of these claims), where we select one statistic per claim; after BEAR processing and filtering, 1,946 claim rows are retained.

Data processing: For the matched replication output, we used the package’s converted correlation scale where available for original and replication statistics. For the all-claims set, effects are heterogeneous across the source papers.

When several inputs are available for z-value construction in the all-claims dataset, we prefer reported z, then reported t, then coefficient divided by standard error, then signed square-root F for numerator df 1, then a 95% confidence interval with a point estimate, then a two-sided p-value conversion. When the selected statistic only supplies a p-value and no sign can be inferred, the z-value is unsigned. For the all-claims text, it is typical to have multiple statistics backing up a single claim, e.g. “F(1,38) = 3.73, p = .033, partial eta-squared = .16; F(1,39) = 7.28, p = .010, partial eta-squared = .16; F<1”. We created a rule to pick one statistic per claim using agreement with the SCORE significant/nonsignificant coding, statistic provenance, exactness, available effect and standard error, and text order.

Additional grouping variables: discipline and SCORE source indicator.

Model of z-values

This documentation page covers more than one fitted dataset, so the fitted models are shown separately.

SCORE claims: social & behav. sci.
Characteristic Estimate
Probability of significance 47%
Relative probability of publication for |z| < 1.96 0.12
Successful replication for |z| > 1.96 73%
Correct sign for |z| > 1.96 99%
SCORE replications: social & behav. sci.
Characteristic Estimate
Probability of significance 51%
Relative probability of publication for |z| < 1.96 0.70
Successful replication for |z| > 1.96 78%
Correct sign for |z| > 1.96 99%
What do these terms mean?
Probability of significance
The reported value is the assurance: the proportion of significant results adjusted for publication bias.
Relative probability of publication
The relative probability of observing a result below the |z| = 1.96 threshold rather than above it. Values below one indicate lower observation probability below the conventional two-sided significance threshold.
Successful replication
The probability that an exact replication has the same sign and |z| greater than 1.96, conditional on the original result having |z| greater than 1.96.
Correct sign
The probability that the observed effect has the same direction as the true effect, conditional on an original result with |z| greater than 1.96.

SCORE claims: social & behav. sci.

SCORE claims: social & behav. sci. mixture model plot

SCORE replications: social & behav. sci.

SCORE replications: social & behav. sci. mixture model plot

References

Tyner, Andrew H., Anna Lou Abatayo, Mason Daley, et al. 2026. “Investigating the Replicability of the Social and Behavioural Sciences.” Nature 652: 143–50. https://doi.org/10.1038/s41586-025-10078-y.