On and Off Script: A Teacher’s Adaptation of Mandated Curriculum for Refugee Newcomers in an Era of Standardization
Bibliographic record
Abstract
English Learners (ELs) make up 9.6% of the total student population in the U.S. (National Center for Education Statistics, 2019). Students with interrupted formal education (SIFE) are a subgroup of ELs who have had at least two fewer years of schooling than their peers, and function at least two years below grade level in reading and mathematics (DeCapua, Smathers, & Tang, 2007). To meet the demands of high stakes testing, schools have been increasingly implementing commercially published, scripted programs for ELs/SIFE (Reeves, 2010). Against this backdrop of the standards-driven and testing-based system, this article reports one of the key findings of a yearlong classroom ethnography of SIFE in an urban public secondary school in the United States, focusing on the experiences of the students and their teacher with two types of curriculum. Drawing on critical theory and culturally relevant/responsive pedagogy, the data tools include classroom observations, interviews with students and the teacher, and the videos of classroom interactions. Findings from our analysis demonstrate that the teacher played an active role in ensuring students learning through her role as a negotiator of the scripted curriculum. This study reaffirms that teachers can find ways to resist the totalizing effects of scripted curriculum.
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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 | 0.001 | 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".