Implicit and Explicit Evaluation: A Brief Review of the Associative–Propositional Evaluation Model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A central theme in contemporary psychology is the distinction between implicit and explicit evaluation. Research has shown various dissociations between the two kinds of evaluations, including different antecedents, different consequences, and discrepant evaluations of the same object. The current article provides a brief review of the associative–propositional evaluation (APE) model, which accounts for these dissociations by conceptualizing implicit and explicit evaluations as the behavioral outcomes of two functionally distinct, yet mutually interacting, mental processes. Whereas implicit evaluations are assumed to be the outcome of associative processes, explicit evaluations are conceptualized as the outcome of propositional processes. Associative processes determine the activation of mental contents on the basis of feature similarity and spatiotemporal contiguity; propositional processes involve the validation of activated mental contents on the basis of cognitive consistency. The APE model includes specific assumptions about mutual interactions between the two processes, implying precise predictions about converging versus diverging patterns of implicit and explicit evaluation.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it