Propositional Versus Dual-Process Accounts of Evaluative Conditioning
Bibliographic record
Abstract
Evaluative conditioning (EC) is defined as the change in the evaluation of a conditioned stimulus (CS) due to its pairing with a valenced unconditioned stimulus (US). According to propositional accounts, EC effects should be qualified by the relation between the CS and the US. Dual-process accounts suggest that relational information should qualify EC effects on explicit evaluations, whereas implicit evaluations should reflect the frequency of CS-US co-occurrences. Experiments 1 and 2 showed that, when relational information was provided before the encoding of CS-US pairings, it moderated EC effects on explicit, but not implicit, evaluations. In Experiment 3, relational information moderated EC effects on both explicit and implicit evaluations when it was provided simultaneously with CS-US pairings. Frequency of CS-US pairings had no effect on implicit evaluations. Although the results can be reconciled with both propositional and dual-process accounts, they are more parsimoniously explained by propositional accounts.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".