Professional Identities of French Lx Economic Immigrants: Perceptions from a Local French-Speaking Community
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
Communicative expertise in the host society’s dominant language is central to newcomers’ socio-professional integration. To date, SLA research has largely ignored laypeople’s perspectives about Lx communicative expertise, though they are the ultimate judges of real-life interactional success. Sociolinguistic studies have shown that laypeople may base their judgments of Lx speech not only on linguistic criteria, but also on extralinguistic factors such as gender and language background. To document laypeople perspectives, we investigated the professional characteristics attributed to four ethnolinguistic groups of French Lx economic immigrants (Spanish, Chinese, English and Farsi) who were nearing completion of the government-funded French language training program in Quebec City, Canada. We asked L1 naïve listeners (N = 49) to evaluate spontaneous speech excerpts, similar in terms of content and speech qualities, produced by a man and a woman from each target group. After they listened to each audio excerpt, we asked listeners to select the characteristics they associated with that person from a list of the most frequent professional qualities found in job advertisements. Data analysis showed that few Lx users were perceived as having strong communication skills in French. Logistic regression revealed no significant relationships between language group, gender, communicative effectiveness, and professional characteristics. However, there were significant associations between communicative effectiveness with the following characteristics: can work independently, can relate to others, is dynamic, has a sense of initiative, and shows leadership skills.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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