Bibliographic record
Abstract
High vowels are generally shorter than low vowels: there is a positive correlation between F1 and duration in English and cross-linguistically (Heffner 1937;Elert 1964;Äimä, 1918).This paper argues that the cross-linguistic height/duration correlation might be explained perceptually: high vowels inherently sound shorter than low vowels.Study 1 analyzed Chilean Spanish vowels to determine whether this correlation is physiological in nature or the result of linguistic rules, finding that the correlation is linguistically-specified.To account for the crosslinguistic occurrence of the correlation, Study 2 tested if speakers perceive shorter high vowels in a forced-choice perception task.Results indicate that high vowels indeed sound shorter, and that this vowel categorization ability is partially learned.Toivonen, who spent countless hours coaching me and pointing me in the right direction.She also found me a job, directed me to the program itself, involved me in research projects, sent me to countless conferences, introduced me to all the right professors, enabled me to explore my interests in Sámi linguistics, helped me get scholarships, found some amazing books for me, and told me some really great jokes that won't be repeated here.The list goes on.I am unable to thank her enough for the contributions she has made to my academic life.I would also like to thank Alex Olsen, who gave me a very good reason to visit Chile.Not only was she a great guide across the country, but assisted in the translation of materials from and into Spanish, found participants, provided lodging and transportation, and gave invaluable moral support throughout the whole process of both the Chilean Spanish experiment and my degree.I would like to thank my father Jim for being an unfathomably deep well of knowledge and experience who would always tell me what to expect, as he's done "this sort of thesis thing" before.On this note, my brother Ben was helpful in giving me the downtime I needed to chill out from writing, and my mother Michaela gave me unmeasurable moral support.Last but certainly not least, I would like to thank my LLI lab for first of all, existing, and second of all, for containing some of the most intelligent and warm-hearted people I have ever met.Each one of them have left a lasting impression on me, and have shared my triumphs and frustrations.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".