Semantic relations and compound transparency: A regression study in CARIN theory
Bibliographic record
Abstract
According to the CARIN theory of Gagn? and Shoben (1997), conceptual relations play an important role in compound interpretation. This study develops three measures gauging the role of conceptual relations, and pits these measures against measures based on latent semantic analysis (Landauer & Dumais, 1997). The CARIN measures successfully predict response latencies in a familiarity categorization task, in a semantic transparency task, and in visual lexical decision. Of the measures based on latent semantic analysis, only a measure orthogonal to the conceptual relations, which instead gauges the extent to which the concepts for the compound?s head and the compound itself are discriminated, also reached significance. Results further indicate that in tasks requiring careful assessment of the meaning of the compound, general knowledge of conceptual relations plays a central role, whereas in the lexical decision task, attention shifts to co-activated meanings and the specifics of the conceptual relations realized in the compound?s modifier family.
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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 | 0.013 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".