Superset versus substitution-letter priming: An evaluation of open-bigram models.
Why this work is in the frame
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Bibliographic record
Abstract
In recent years, a number of models of orthographic coding have been proposed in which the orthographic code consists of a set of units representing bigrams (open-bigram models). Three masked priming experiments were undertaken in an attempt to evaluate this idea: a conventional masked priming experiment, a sandwich priming experiment (Lupker & Davis, 2009) and an experiment involving a masked prime same-different task (Norris & Kinoshita, 2008). Three prime types were used, first-letter superset primes (e.g., wjudge-JUDGE), last-letter superset primes (e.g., judgew-JUDGE) and standard substitution-letter primes (e.g., juwge-JUDGE). In none of the experiments was there any evidence that the superset primes were more effective primes, the prediction made by open-bigram models. In fact, in the second and third experiments, first-letter superset primes were significantly worse primes than the other two prime types. These results provide no evidence for the existence of open-bigram units. They also suggest that prime-target mismatches at the first position produce orthographic codes that are less similar than mismatches at other positions. Implications for models of orthographic coding are discussed.
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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 | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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