Negotiating Language Policies: Parents as Agents of Change for Learners of EAL
Bibliographic record
Abstract
Language policy research puts little emphasis on parental agency. The parents of English as Additional Language (EAL) learners are often excluded from school decision-making processes whereas White middle-class parents are more strategic in intervening in their children’s schools. This study explored how immigrant parents advocated for higher quality and more equitable EAL policies and practices in Alberta. The study takes policy as discursive practice and examines how policy is experienced and constructed locally by parents. It focuses on eight components of EAL policy: visibility, designation of responsibility, eligibility, duration, placement, programming, assessment and reporting, and funding. Data for the study were collected through policy documentation, interviews with 35 parents and community members from 17 countries, and 2 focus groups with parents and policy-makers. Parents reported that inequitable EAL policies resulted in the creation of a permanent underclass and utilized a range of strategies to influence such policies. The study brings new voices of EAL parents into the educational policy process. Results of this research will provide directions for EAL policies, programs and services, as well as new insights into the effectiveness of advocacy and capacity building of EAL parents.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".