Positioning all Students and Teachers as Intercultural Citizens— A Two-way Adaptation Approach to ELL Identity Negotiation
Bibliographic record
Abstract
Abstract: This article addresses the power imbalance between English language learners (ELL) and native English speakers (NES) in culturally and linguistically diverse K-12 classrooms. Current ELL positioning models explored in empirical research studies are positioned in this article in correlation with the stages in Bennett’s theory of the Developmental Model of Intercultural Sensitivity. The result indicates that we need an integrative model that equalizes the power relations between ELLs and NES to guide all learners and teachers towards cultural integration. Drawing on positioning theory and the concept of intercultural citizenship, this article proposes an integrative approach of positioning all students and teachers as intercultural citizens as a discursive identity negotiation means to engender an equitable two-way cultural adaption that not only challenges the raciolinguistic ideologies but also builds intercultural citizenship among all learners. A step-by-step school-level practical guide is suggested to implement this integrative approach.
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 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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".