An examination of models of reading multi-morphemic and pseudo multi-morphemic words using sandwich priming.
Bibliographic record
Abstract
Rastle et al. (2004) reported that true (e.g., walker) and pseudo (e.g., corner) multi-morphemic words prime their stem words more than form controls do (e.g., brothel priming BROTH) in a masked priming lexical decision task. This data pattern has led a number of models to propose that both of the former word types are "decomposed" into their stem (e.g., walk, corn) and affix (e.g., -er) early in the reading process. The present experiments were designed to examine the models proposed to explain Rastle et al.'s effect, including models not assuming a decomposition process, using a more sensitive priming technique, sandwich priming (Lupker & Davis, 2009). Experiment 1, using the conventional masked priming procedure, replicated Rastle et al.'s results. Experiments 2 and 3, involving sandwich priming procedures, showed a clear dissociation between priming effects for true versus pseudo multi-morphemic words, results that are not easily explained by any of the current models. Nonetheless, the overall data pattern does appear to be most consistent with there being a decomposition process when reading real and pseudo multi-morphemic words, a process that involves activating (and inhibiting) lexical-level representations including a representation for the affix (e.g., -er), with the ultimate lexical decision being based on the process of resolving the pattern created by the activated representational units. (PsycInfo Database Record (c) 2023 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 | 0.000 |
| 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".