Inter-Sentential Patterns of Code-Switching: A Gender-Based Investigation of Male and Female EFL Teachers
Bibliographic record
Abstract
This article has sought to contribute to discussions concerning the value of inter-sentential patterns of code-switching (henceforth ISPCS) particularly in the context of EFL classrooms. Through a detailed analysis of recorded data produced in that context, distinctive features in the discourse were discerned which were associated with males’ and females’ inter-sentential switches. By looking at language choice against the background of this patterning, one can understand the complexity of the occurrences of inter-sentential switches in the classroom. A few studies on ISPCS in EFL classrooms have been hardly conducted to determine the gender-based inclination among EFL teachers. For this reason, there is a lack of awareness on the part of English language teachers about the qualitative and quantitative use of ISPCS in the context of Pakistani EFL classrooms. For the purpose of investigation, the ethnography of interaction was selected as a research design to record and transcribe the sessions of eight resource persons of Allama Iqbal Open University. During the analysis, the results of the study indicated that all the male and female teachers switched code in the boundary of ISS (henceforth ISS). Moreover, in the light of the data analysis, trends were determined among male and female teachers for the patterns of inter-sentential switches. In short, this paper tried to develop an understanding about the phenomenon of inter-sentential switches to get a better insight of the teaching/learning situation in the EFL context.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".