Relational complexity influences analogical reasoning ability
Bibliographic record
Abstract
Human language without analogy is like a zebra without stripes. The ability to understand analogies, or to engage in relational reasoning, has been argued to be an important distinction between the cognitive abilities of human and non-human animals. Current studies have failed to robustly show that animals can perform more complex, relational discriminations, in part because such tests rely on linguistic or symbolic experiences, and therefore are not suitable for evaluating analogical reasoning in animals. We report on a methodological approach allowing for direct comparisons of analogical reasoning ability across species. We show that human participants spontaneously make analogical discriminations with minimal verbal instructions, and that the ability to reason analogically is affected by analogical complexity. Furthermore, performance on our task correlated with participants' fluid intelligence scores. These results show the nuance of analogical reasoning abilities by humans, and provide a means of robustly comparing this capacity across species.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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; both teacher heads agree on what is shown here.
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".