Still waters run deep: giving poetic voice to the silent struggles of academically successful immigrant students
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACTTypically, newcomer students to North American who must learn the school language as their second language (L2), tend to become conversationally fluent and socially adept in their L2 rather quickly (after one or two years), but continue to struggle to use their L2 in more cognitively complex academic tasks for up to five years (Cummins, 1979; 1984). Teachers who work with L2 learners in mainstream classes may be accustomed to this pattern and therefore aware of the additional academic language support that these students require. However, not all immigrant struggles are academic in nature. This study focuses on a different subset of immigrant students in North America who may fail to receive support for their needs, namely, students who have previously attended private English immersion schools in Latin America where they have already reached a high academic proficiency in their L2, but where they have had few opportunities to use their L2 socially. While thriving academically in their new schools, these students may still struggle with social isolation. For this qualitative study, I conducted semi-structured interviews with six participants who immigrated to either the United States or Canada when they were between the ages of 11 and 19 from Colombia and Mexico. They all attended private bilingual schools in their countries of origin. I used poetic inquiry to examine the common themes in their immigration experiences. Specifically, after analyzing my data for themes through open coding and poetic inquiry, I recombined fragments of individual's interviews to create 'found poetry' on each theme (Butler- Kisber, 2010), thus using participants' own voices to express their common experiences with language, culture, identity confusion, and social isolation as they adjusted to their new society (Butler-Kisber & Stewart, 2009). Based on findings from the study, I emphasize the need to heighten teachers' awareness of immigrant students' academic and social needs, and I outline measures that teachers and schools can take to support these students' social integration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.011 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it