Bibliographic record
Abstract
Abstract While economists recognize the important role of formal institutions in the promotion of trade, there is increasing agreement that institutions are typically endogenous to culture, making it difficult to disentangle their separate contributions. Lab experiments that assign institutions exogenously and measure and control individual cultural characteristics can allow for clean identification of the effects of institutions, conditional on culture, and help us understand the relationship between behavior and culture, under a given institutional framework. We focus on cultural tendencies toward individualism/collectivism, which social psychologists highlight as an important determinant of many behavioral differences across groups and people. We design an experiment to explore the relationship between subjects’ degree of individualism/collectivism and their willingness to abandon a repeated, bilateral exchange relationship in order to seek potentially more lucrative trade with a stranger, under enforcement institutions of varying strength. Overall, we find that individualists tend to seek out trade more often than collectivists. A diagnostic treatment and additional analysis suggests that this difference may reflect both differential altruism/favoritism to in-group members and different reactions to having been cheated in the past. This difference is mitigated somewhat as the effectiveness of enforcement institutions increases. Nevertheless we see that cultural dispositions are associated with willingness to seek out trade, regardless of institutional environment.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".