Replications provide mixed evidence that inequality moderates the association between income and generosity
Bibliographic record
Abstract
Schmukle et al. (1) conducted informative conceptual replications of our finding that economic inequality moderates the relationship between income and generosity (2). Schmukle et al. (1) did not find that inequality moderates associations between income and self-reported charitable donations (study 1), first- and second-mover trust game allocations (study 2), and self-reported volunteering (study 3). Their findings contribute to a larger literature documenting patterns both consistent (e.g., ref. 3) and inconsistent (e.g., ref. 4) with our theoretical claim. Note that Schmukle et al.’s (1) conceptual replications differ operationally from ours. First, their generosity measures differed: We used a secondary dataset assessing generosity with a “dictator game” in which participants gave between 0 and 10 raffle tickets to another participant. The dictator game minimizes self-serving … [↵][1]1To whom correspondence may be addressed. Email: Scote{at}rotman.utoronto.ca. [1]: #xref-corresp-1-1
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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 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 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".