Bibliographic record
Abstract
Categorical approaches to lexical stress typically assume that words have either regular or irregular stress, and imply that only the latter needs to be stored in the lexicon, while the former can be derived by rule. In this paper, we compare these two groups of words in a lexical decision task in Portuguese to examine whether the dichotomy in question affects lexical retrieval latencies in native speakers, which could indirectly reveal different processing patterns. Our results show no statistically credible effect of stress regularity on reaction times, even when lexical frequency, neighborhood density, and phonotactic probability are taken into consideration. The lack of an effect is consistent with a probabilistic approach to stress, not with a categorical (traditional) approach where syllables are either light or heavy and stress is either regular or irregular. We show that the posterior distribution of credible effect sizes of regularity is almost entirely (97.05%) within a region of practical equivalence, which provides strong evidence that no effect of regularity exists in the lexical decision data modelled. Frequency and phonotactic probability, in contrast, showed statistically credible effects given the experimental data modelled, which is consistent with the literature.
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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 | 0.001 | 0.023 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".