Bibliographic record
Abstract
I have known John since 1972, and am extremely pleased to be able to offer my personal tribute to him. I was his PhD thesis supervisor at the University of Edinburgh. John needed the bare minimum of supervision, being clearly destined for an outstanding career in academic phonetics. He and I share a significant research interest in the categorization of voice quality and vocal register, the subject of his thesis -- John is also an expert in the transcription of voice quality and voice quality measurement. But this, valuable though it certainly is, is far outweighed by John's ground-breaking analysis of the activities involved in the production of pharyngeal, laryngeal, epiglottal and aryepiglottic sounds. His experimental investigations using videofluoroscopy, laryngeal ultrasound, laryngoscopy, endoscopy and acoustic techniques, together with his clear expositions of how these sounds are produced and their auditory counterparts, have clarified what was previously more vaguely understood by the majority of phoneticians, including myself. John has gone on to a very distinguished career, with more than 100 scholarly publications, major editorships of both the Handbook of the International Phonetic Association and the Cambridge English Pronouncing Dictionary, the Presidency of the International Phonetic Association, and the editorship of the Journal of the International Phonetic Association. These and many other achievements have led to his very well deserved Fellowship of the Royal Society of Canada, recognizing his outstanding contribution. Looking through his authored and edited publications, my view is that John very thoroughly merits his standing as a phonetician's phonetician, and I congratulate him very warmly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.070 | 0.061 |
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".