What does constituent priming mean in the investigation of compound processing?
Bibliographic record
Abstract
Abstract Most dictionary definitions for the term compound word characterize it as a word that itself contains two or more words. Thus, a compound word such as goldfish is composed of the constituent words gold and fish. In this report, we present evidence that compound words such as goldfish might not contain the words gold and fish, but rather positionally bound compound constituents (e.g., gold- and -fish) that are distinct and often in competition with their whole word counterparts. This conceptualization has significant methodological consequences: it calls into question the assumption that, in a traditional visual constituent priming paradigm, the participant can be said to be presented with constituents as primes. We claim that they are not presented with constituents. Rather, they are presented with competing free-standing words. We present evidence for the processing of Hebrew compound words that supports this perspective by revealing that, counter-intuitively, prime constituent frequency has an attenuating effect on constituent priming. We relate our findings to previous findings in the study of German compound processing to show that the effect that we report is fundamentally morphological rather than positional or visual in nature. In contrast to German in which compounds are always head-final morphologically, Hebrew compounds are always head initial. In addition, whereas German compounds are written as single words, Hebrew compounds are always written with spaces between constituents. Thus, the commonality of patterning across German and Hebrew is independent of visual form and constituent ordering, revealing, as we claim, core features of the constituent priming paradigm and compound processing.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".