Claiming Their Voice: Sociolinguistic Factors Affecting Immigrant Workers’ Ability to Speak Up
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
Immigrants’ multiple identities are sources of contention as they strive in the English-speaking workplace, where they need to meet job demands and demands from employers who expect them to conform to the culture of the management (Harper, Peirce, & Burnaby, 1996; Jacobson, 2003; Katz, 2000). With California having a significant immigrant worker population, this study investigated how many of these workers navigate multiple identity and cultural issues while attempting to use their learned English to claim their voice. In an adult ESL classroom, first qualitative data were collected from students’ responses about a workplace scenario. Then, 3 individuals from the class were chosen for in-depth interviews to determine factors that contribute to or hinder their ability to stake their claim in the workplace and speak up for themselves. The study results showed that several sociolinguistic factors influence whether or not workers chose to speak up and that these factors are as pertinent as workers’ linguistic proficiency and the types of employers and coworkers they have. The authors discuss pedagogical implications with the goal of empowering immigrants to claim their voice at the workplace.
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 | 0.003 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it