What is that I hear? An interdisciplinary review and research agenda for non‐native accents in the workplace
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Speaking with a non‐native English accent at work is a prevalent global phenomenon. Yet, our understanding of the impact of having a non‐native accent at work is limited, in part because research on accents has been multidisciplinary, fragmented, and difficult for scholars to access and synthesize. To advance research on accents in the workplace, we provide an interdisciplinary and integrative review of research on non‐native accents drawing from the communications, social psychology, and organizational sciences literatures. First, we briefly review the dominant approaches taken in each literature. Second, we organize and integrate extant research findings using a 2 × 2 framework that incorporates the two main theoretical perspectives used to explain the effects of accents—stereotypes and processing fluency—and the two primary categories of workplace outcomes examined—interpersonal (i.e., others' evaluations of speakers with non‐native accents, such as hiring recommendations) and intrapersonal (i.e., non‐native‐accented speakers' own evaluations and experiences, such as sense of belonging). To facilitate future research, we end by articulating a research agenda including theoretical and methodological expansions related to the study of accents, identifying critical moderators, adopting an intersectional approach, and studying group‐level and potential positive effects of speaking with non‐native accents.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 it