Classification of nominal compounds containing mimetics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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 ] n k ↔ [ hada ‘skin’ with attribute SEM i ] 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.
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.
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 it