Sandwich priming: A method for overcoming the limitations of masked priming by reducing lexical competitor effects.
Bibliographic record
Abstract
An orthographically similar masked nonword prime facilitates responding in a lexical decision task (Forster & Davis, 1984). Recently, this masked priming paradigm has been used to evaluate models of orthographic coding--odels that attempt to quantify prime-target similarity. One general finding is that priming effects often do not occur when prime-target similarity is moderate, a result that the authors interpret as being due to uncontrolled effects of lexical inhibition. In the present research, a new version of the masked priming paradigm, sandwich priming, was introduced in an effort to minimize the impact of lexical inhibition. Masked sandwich priming involves briefly presenting the target itself prior to the presentation of each prime. Results indicate that the new paradigm was successful. The predicted priming effects were observed for Guerrera and Forster's (2008) T-All primes (e.g., avacitno-VACATION) and for primes differing from their targets at 3 letter positions (e.g., coshure-CAPTURE)-effects that are not found with the conventional masked priming paradigm. In addition to demonstrating the usefulness of the sandwich priming technique, these results also support the assumption that inhibitory processes play an important role in lexical processing.
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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 | 0.000 | 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) | 0.000 | 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".