Bibliographic record
Abstract
We describe an as yet unidentified bias relevant to comparative cognition research: WEIRD-centrism. This bias leads us to take as the gold standard the practices, capacities, or concepts of WEIRD (Western, Educated, Industrialized, Rich, and Democratic) humans, that is, humans who grew up in WEIRD societies and whose behavior has been shaped by the influence of WEIRD cultural norms and practices. We identify how the bias impacts the study of practices, capacities, and concepts, and offer two suggestions for mitigating the bias. The first is to use what we are calling a multibaseline approach, which involves starting with constructs that come not from our experiences as humans, but from our growing understanding of other species. The second is to make use of philosophical analysis and conceptual engineering, which includes identifying minimal concepts of psychological capacities as well as a dimensional approach that depicts the many ways in which a capacity can be instantiated. We hope that these tools will allow us to better understand the similarities and differences both within and between species. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.057 | 0.108 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.006 | 0.088 |
| Scholarly communication | 0.009 | 0.044 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".