Bibliographic record
Abstract
Abstract Psycholinguistics is the study of how language is acquired, represented, and used by the human mind; it draws on knowledge about both language and cognitive processes. A central topic of debate in psycholinguistics concerns the balance between storage and processing. This debate is especially evident in research concerning morphology, which is the study of word structure, and several theoretical issues have arisen concerning the question of how (or whether) morphology is represented and what function morphology serves in the processing of complex words. Five theoretical approaches have emerged that differ substantially in the emphasis placed on the role of morphemic representations during the processing of morphologically complex words. The first approach minimizes processing by positing that all words, even morphologically complex ones, are stored and recognized as whole units, without the use of morphemic representations. The second approach posits that words are represented and processed in terms of morphemic units. The third approach is a mixture of the first two approaches and posits that a whole-access route and decomposition route operate in parallel. A fourth approach posits that both whole word representations and morphemic representations are used, and that these two types of information interact. A fifth approach proposes that morphology is not explicitly represented, but rather, emerges from the co-activation of orthographic/phonological representations and semantic representations. These competing approaches have been evaluated using a wide variety of empirical methods examining, for example, morphological priming, the role of constituent and word frequency, and the role of morphemic position. For the most part, the evidence points to the involvement of morphological representations during the processing of complex words. However, the specific way in which these representations are used is not yet fully known.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.030 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".