Exploring speech expectations during the hiring process and perceived accent discrimination in the workplace: Outcomes for L2 French job applicants and employees in Québec
Bibliographic record
Abstract
Because people often infer a person’s personal and professional characteristics such as intelligence and competence from that person’s accent, employers, colleagues, or customers may react negatively toward speakers who display second language (L2) speech, which can be detrimental to those speakers’ chances of obtaining a job, their prospects of job advancement, and their sense of belonging to their workplace community. However, the majority of research on accent bias in the workplace focuses on L2 English accents and relies on first-impression listener judgments. This dissertation addresses these shortcomings by providing a comprehensive listener- and speaker-focused perspective through two complementary studies that explore how L2 French speakers are evaluated during extended job interviews and how L2 French speakers experience workplace accent discrimination in Québec. \n Study 1 explored whether L1 French listeners’ evaluations of L1 and L2 French-speaking job applicants would differ under various expectation conditions (congruent, incongruent, no-expectancy). A typical interview process was emulated by presenting 55 HR-experienced listeners first with job applicants’ resumes, then with audio-recorded interview excerpts, which captured how employability evaluations and speech perception might evolve dynamically throughout the interview process. The L2 applicants were perceived as less employable than the L1 applicants. When an applicant was presumed to be an L2 speaker based on her resume, her employability was subsequently upgraded when she spoke L1 French. Lower employability evaluations of L2 applicants were related to their accent being perceived as less prestigious and more difficult to understand than expected. \n Study 2 investigated perceived accent discrimination and its possible consequences from the perspective of 60 L2 French-speaking employees. Participants provided anecdotes and responded to surveys about how they are treated at work due to their French accent and how willing they are to engage in certain work interactions. Having more frequent experiences with accent discrimination in the workplace was associated with employees avoiding taking on leadership roles, participating at meetings, and applying to certain jobs. Common stereotypes mentioned by employees were being labeled as foreigners, perceived as incompetent and unwilling to learn French, and identified as a threat to the survival of French in Québec.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".