Bibliographic record
Abstract
This descriptive qualitative study investigates the types and functions of code-switching between English and vernacular Arabic in eight vernacular poems. In order to do this, eight published audio and video recordings of poems obtained from YouTube are analysed using a qualitative method of data analysis. The content analysis reveals two main types of code-switching: code-switching between sentences (inter-sentential) and code-switching within sentences (intra-sentential). Its possible functions are humour, reporting a conversation between the poet and an English speaker, quoting an English speaker or imagining a conversation with them, and attempting to be innovative. Intra-sentential code-switching is found to occur either at the beginning, middle or end of the line in a poem. However, it could occur in more than one place in the same line. Moreover, the poems follow grammatical constraints and code-switching is systematic, except in one instance where the poet aims to keep the same rhyme. In almost all of the poems analysed in this study, intra-sentential code-switching occurs more frequently than inter-sentential code-switching.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".