The affordances of Code-Switching: A systematic review of its roles and impacts in multilingual contexts
Bibliographic record
Abstract
Code-switching, the practice of alternating between languages or dialects within a conversation, plays a multifaceted role in multilingual contexts, particularly in education, communication, and cultural identity. This systematic review synthesizes existing research to explore the affordances of code-switching across diverse linguistic and sociocultural settings. The article examines its roles in enhancing comprehension, fostering learner engagement, and bridging cultural gaps, while also addressing its cognitive, pedagogical, and sociolinguistic impacts. Key findings reveal that code-switching serves as a powerful tool for facilitating bilingual and multilingual education, supporting identity negotiation, and promoting inclusivity in diverse environments. However, challenges such as stigmatization, policy constraints, and unequal power dynamics between languages are also highlighted. By analyzing patterns, trends, and implications from empirical studies, this review offers insights into best practices for leveraging code-switching as a resource in multilingual settings. It emphasizes the need for context-sensitive approaches and interdisciplinary collaborations to maximize its benefits while mitigating associated challenges.
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.
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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".