Meaning predictability and compound interpretation: A psycholinguistic investigation
Why this work is in the frame
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Bibliographic record
Abstract
The central aim of this paper is to investigate Štekauer's (2005 , 2006 ) notion of meaning predictability within a psycholinguistic framework. In particular, we examined whether novel compounds with low meaning predictability are more difficult to interpret than are compounds with higher meaning predictability. A second aim is to evaluate the influence of the components of meaning predictability (i.e., the goodness of a particular reading, as well as the prevalence of that reading) on comprehension. We report the results of two experiments conducted with novel compounds (e.g., wool basket and adolescent doctor). In Experiment 1, participants performed a sense/nonsense judgment task. In Experiment 2, participants performed a verification task in which they indicated whether a particular reading was appropriate. The results confirm that meaning predictability influences ease of interpretation, but also indicate that the role of the components of meaning predictability differs between the two tasks.
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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 | 0.001 |
| 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