Bibliographic record
Abstract
In Japanese, some nominal compounds have mimetic components (Nominal Compounds with Mimetics (NCMs)) (e.g., zaazaa-buri [mimetic(the sound of heavy rain)-a fall(from the sky)] ‘a downpour’). This paper examines how mimetics participate in word-formation of nominal compounds, applying Construction Morphology. Examination of representative NCMs indicates: (i) NCMs are mostly right-headed, although some are double-headed, and (ii) mimetics combine with the types of nouns that combine with non-mimetic components. Given this, the paper proposes NCMs are part of the inheritance hierarchy for nominal compounds; specifically, their top node diverges according to the head position, building on Booij (2010 : 7). The hierarchy consists of different constructional schemas, such as <[x i-hada] nk ↔ [hada ‘skin’ with attribute SEMi]k>, wherein the variable x can be replaced by a mimetic, as in gasagasa-hada ‘rough skin’, or a non-mimetic, as in yawa-hada ‘soft skin’. The paper argues that mimetics are an integral part of nominal compound word formation, enriching lexical varieties of nominal compounds. The Construction Morphology representational system proves useful to indicate where NCMs appear in the word network.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".