Stimulus-based mirror effects in associative recognition revisited.
Bibliographic record
Abstract
The mirror effect, the finding that a manipulation which increases the hit rate in recognition tests also decreases the false alarm rate, is held to be a regularity of memory. Neath et al. (in press) took advantage of the recent increase in the number of linguistic databases to create sets of stimuli that differed on one dimension but were more fully equated on other dimensions known to affect memory. Using these highly controlled stimulus sets, no mirror effects were observed; in contrast, using stimulus sets that had confounds resulted in mirror effects. In this article, we use their stimulus sets to examine associative recognition. Using confounded stimuli, Experiment 2 found a lower false alarm rate for high- compared to low-frequency words, replicating previous results, and Experiment 4 found a mirror effect when manipulating concreteness, also replicating previous results. Using highly controlled stimuli, Experiment 1 found no evidence that frequency affected associative recognition, and Experiment 3 found concreteness affected only the hit rate, not the false alarm rate. When highly controlled stimuli are used, frequency affects only the false alarm rate in item recognition and has no effect in associative recognition, whereas concreteness affects hit rates in both item and associative recognition. Implications for theoretical accounts are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".