Frequency effects in Spanish phonological speech errors: Weak sources in the context of weak syllables and words
Bibliographic record
Abstract
The present study examines the effects of the frequency of phoneme, syllable, and word units in the Granada corpus of Spanish phonological speech errors. We computed several measures of phoneme and syllable frequency and selected the most sensitive ones, along with word (lexeme) frequency to compare the frequencies of source, target, and error units at the phoneme, syllable, and word levels. Results showed that phoneme targets have equivalent frequency to matched controls, whereas source phonemes are lower in frequency than chance (the Weak Source effect) and target phonemes (the David effect). Target, source, and error syllables and words also were of lower frequency than chance, and error words (when they occur) were lowest in frequency. Contrary to most current theories, which focus on faulty processing of the target units, present results suggest that faulty processing of the source units (phonemes, syllables, and words) is an important factor contributing to phonological speech errors. Low-frequency words and syllables have more difficulty ensuring that their phonemes, especially those of low frequency, are output only in their correct locations.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".