Forgetting and redintegration of consonants and vowels in pseudoword lists
Bibliographic record
Abstract
Immediate recall of phonemes was studied in a pseudoword span task. Finnish participants recalled lists of increasing length, consisting of C(consonant)V(vowel)CVCV pseudowords. The lists were made up from pools of 12 pseudowords. There were three types of lists. In the non-redundant lists the items were unpredictable combinations of consonants and vowels. In consonant-redundant lists, all items had the consonant frame /t/_/s/_/l/. In vowel-redundant lists, all items had the vowel frame _/u/_/e/_/o/. Unlike redundant last syllables in a previous experiment, neither consonant nor vowel redundancy helped list recall. Instead, a harmful phonological similarity effect was apparent in the vowel-redundant case but not the consonant-redundant case. A phoneme-level analysis of recall showed that consonants were recalled better in consonant-redundant lists and vowels were recalled better in vowel-redundant lists compared to non-redundant lists. Vowels appeared to be more important for discrimination between items, with redundancy resulting in confusions. The consequences of phoneme-level forgetting and redintegration for item- and list-level recall are discussed.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".