Bibliographic record
Abstract
Language contact leads to a number of linguistic phenomena, most noticeably code-switching, which refers to bilinguals’ utilization of two languages in the same conversation and even within a single utterance. This study investigates Arabic-English code-switching among Jordanian immigrants in Manitoba, Canada and presents a qualitative analysis of the socio-pragmatic functions this linguistic behavior serves. The participants were 11 (3 females and 8 males) Jordanian immigrants living in Winnipeg, the capital of Manitoba. Two instruments were employed to elicit the data necessary for this study: audio recordings and semi-structured interviews. The code-switching occurrences were categorized into different socio-pragmatic functions based on the analysis of the content of almost 18 hours of recorded conversations. The analysis of the content of the audio-recordings besides the semi-structured interviews showed that Jordanian immigrants resort to code-switching to achieve a number of socio-pragmatic functions: filling lexical needs, integrating into the Canadian culture and lifestyle, qualifying a message, mitigating embarrassment and negative connotations, quoting the exact words of somebody, and creating humorous or ironic effect. Keywords: Code-Switching; Socio-Pragmatic Functions; Canada; Arabic; English.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".