Cross-National Replication of Prosocial Simulation Effect Using Cumulative Link Mixed Modelling
Bibliographic record
Abstract
Previous work has found mentally simulating events of helping others can enhance prosocial intentions. However, to date, this ‘prosocial simulation effect’ (PSE) has only been demonstrated in North America. We provide the first pre-registered replication of PSE outside of North America in a New Zealand sample, following existing protocols (Experiment 1: N=40) and with modifications to rule out an additional confound (Experiment 2: N=40). Moreover, given evidence that metric models are problematic for assessing ordinal data, we conducted cumulative link model (CLM)-based analyses. Both experiments provide statistically-robust support for the PSE outside of North America, lending greater credence to this effect. We also show that, relative to CLM-based analyses, metric models can underestimate effects in ordinal data, yielding inconsistent results across near-identical experimental designs. We consider this issue against the backdrop of the replication crisis, and recommend the use of CLM-based analyses in all research reliant on ordinal scales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.050 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".