Making sense of word senses: The comprehension of polysemy depends on sense overlap.
Bibliographic record
Abstract
Studies of polysemy are few in number and are contradictory. Some have found differences between polysemy and homonymy (L. Frazier & K. Rayner, 1990), and others have found similarities (D. K. Klein & G. Murphy, 2001). The authors investigated this issue using the methods of D. K. Klein and G. Murphy (2001), in whose study participants judged whether ambiguous words embedded in word pairs (e.g., tasty chicken) made sense as a function of a cooperating, conflicting, or neutral context. The ambiguous words were independently rated as having low, moderate, or highly overlapping senses to approximate a continuum from homonymy to metonymic polysemy. The effects of meaning dominance were examined. Words with highly overlapping meanings (e.g., metonymy) showed reduced effects of context and dominance compared with words with moderately or low overlapping meanings (e.g., metaphorical polysemy and homonymy). These results suggest that the comprehension of ambiguous words is mediated by the semantic overlap of alternative senses/meanings.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".