Are You Studying Occasion Setting? A Review for Inquiring Minds
Bibliographic record
Abstract
1983) proposed that occasion setting was a type of learning distinct from simple discriminations (X+, Y-), with the defining property as modulation by one stimulus (X) of the associative value of another stimulus (XA+, A-), which is orthogonal to any direct control of behavior or any outcome representation elicited by X.A variety of procedures have been developed to evaluate acquisition of this kind of control, as well as distinguish it from direct control.Application of occasion setting in psychology has remained largely confined to traditional associative learning paradigms.The current review aims to provide researchers with the knowledge and tools necessary to identify whether occasion setting might be occurring in their own research.One test procedure is recommended, though several options are reviewed.We encourage thinking more broadly about the presence of occasion setting by evaluating its potential role in spatial learning, match-to-sample (MTS), and theory of mind (ToM), among others.Furthermore, we briefly review demonstrations of occasion setting in other organisms, including invertebrates.These demonstrations suggest that occasion setting has played an important role in evolutionary fitness.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".