The Frequency and Importance of Accurate Heritage Name Pronunciation for Post-Secondary International Students in Canada
Bibliographic record
Abstract
International students’ names are often mispronounced, and this experience can have psychological and relational implications for some students’ cross-cultural adjustment. Little research, however, has examined why students are or are not bothered by mispronunciations. This study examined the impact of heritage name mispronunciation on 173 language-minority international students in Canada. The results indicated that although heritage name mispronunciations occurred frequently, only about half of the sample perceived correct pronunciation as important. Those who felt accurate pronunciation was important stressed that their name had a strong connection to their heritage and that mispronunciations were disrespectful of that significance. Those who felt accurate pronunciation was not important cited little personal connection to the name and accepted mispronunciations for reasons of efficiency. The findings suggest that accurate heritage name pronunciation can facilitate the adjustment of international students by fostering positive affect, communicative comfort, and relational closeness during cross-cultural interactions in the host countries.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".