Mentioning the Sample's Country in the Article’s Title Leads to Bias in Research Evaluation
Bibliographic record
Abstract
Psychology research from Western, educated, industrialized, rich, and democratic (WEIRD) countries, especially from the United States, receives more scientific attention than research from non-WEIRD countries. We investigate one structural way that this inequality might be enacted: mentioning the sample's country in the article title. Analyzing the current publication practice of four leading social psychology journals (Study 1) and conducting two experiments with U.S. American and German students (Study 2), we show that the country is more often mentioned in articles with samples from non-WEIRD countries than those with samples from WEIRD countries (especially the United States) and that this practice is associated with less scientific attention. We propose that this phenomenon represents a (perhaps unintentional) form of structural discrimination, which can lead to underrepresentation and reduced impact of social psychological research done with non-WEIRD samples. We outline possible changes in the publication process that could challenge this phenomenon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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 teacher head, 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".