Bibliographic record
Abstract
Understanding how morphologically complex words are processed is crucial to understanding the structure of the mental lexicon. Decomposition accounts of morphological processing receive the most support within the psycholinguistic literature, although some of these accounts have difficulty with words where the morphological status is unclear (e.g., hardly; grocer). These issues of murky morphology may be better accounted for by learning models of processing such as emergentist or discriminative models that derive morphological relationships from semantic and phonologically consistent regularities among words. Graded morphological priming effects have been demonstrated in English which support learning accounts of lexical processing (Gonnerman et al., 2007; Quémart et al., 2018). In this study, we examine semantic similarity and processing of morphologically complex words in Quebec French to determine whether graded effects can be found in other languages, and in particular in a language with a richer morphological system than English. Results reveal graded semantic similarity and graded morphological priming effects supporting an emergentist account of 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 | 0.000 | 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".