A review of Teaching adult immigrants with limited formal education: Theory, research and practice
Bibliographic record
Abstract
Around the world, 750 million adults live in unstable conditions where conflict and poor infrastructure limit their access to formal schooling and threaten them with displacement.This figure grows every year, as does the number of displaced people who settle in a new land and need to learn a new language.Many governments have responded by creating newcomer education programs, but only recently have the specific language learning needs of adult newcomers with limited formal education gained significant scholarly attention.As a result, resources for teaching these learners are scarce and scattered.Peyton and Young-Scholten's recent volume -Teaching Adult Migrants With Limited Formal Education: Theory, Research and Practice -represents a major step toward rectifying this problem, providing a concise reference work informed by a nearly decade-long project entitled European Speakers of Other Languages: Teaching Adult Migrants and Training Their Teachers.Although the resulting text is steeped in the European tradition of language education, it remains valuable to any researchers and teachers of migrant adult language learners regardless of geographic area.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".