Sentential Context and the Interpretation of Familiar Open-Compounds and Novel Modifier-Noun Phrases
Bibliographic record
Abstract
Two experiments investigated the influence of sentential context on the relative ease of deriving a particular meaning for novel and familiar compounds. Experiment 1 determined which of two possible meanings was preferred for a set of novel phrases. Experiment 2 used both novel (e.g., brain sponge) and familiar compounds (e.g., bug spray). The compounds appeared in a sentential context that supported either the dominant or subdominant meaning. Next, participants saw either the dominant or subdominant definition and indicated whether it was plausible. When the definition was consistent with the preceding sentence, the participants were more likely to consider the definition plausible regardless of whether the compound was novel or familiar, although this difference was more pronounced for novel phrases than for familiar phrases. In terms of response times, the effect of sentential context also depended on the degree of dominance. The data suggest that the interpretation of compounds is affected by at least two sources of information: sentential context and the relative dominance of the preferred meaning.
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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 | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".