Perception of dialectal variation: Can speakers of Western Canadian English perceive New Zealand English /r/-sandhi?
Bibliographic record
Abstract
The current study investigates perception of New Zealand English /r/-sandhi by speakers of Western Canadian English. It investigates whether speakers of Western Canadian English can differentiate between intrusive-/r/ (e.g., sawing [sæoɹəŋ]) and linking-/r/ (e.g., soaring [sæoɹəŋ]) of /r/-sandhi across morpheme boundaries and across word boundaries (e.g., linking: boar and, intrusive: boa and). Reaction time and accuracy were recorded in a two-alternative forced choice experiment. Stimuli showed significant acoustic differences between the linking-/r/ and intrusive-/r/ environments, with intrusive-/r/ having a shorter duration than linking-/r/. Participants were highly accurate and faster at recognizing words with linking-/r/ (e.g., soaring) and extremely inaccurate and slower at recognizing intrusive-/r/ (e.g., sawing). Participants’ responses to linking-/r/ at a morpheme boundary were significantly more accurate and faster than responses with linking-/r/ across word boundaries. The results of this experiment address the phonetic variability present in cross-dialect perception and begin to investigate strategies listeners utilize to accurately perceive speech.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".