Bibliographic record
Abstract
Many stakeholders are involved in the provision of educational services for immigrant children and youth in Edmonton, Canada. Unfortunately, there has been limited coordination across stakeholders, leaving many students falling between the cracks. Federal government contributions are restricted by the Canadian Constitution; thus, federal input is limited to non-instructional support. The provincial government makes policy and funding decisions about English as a second language (ESL) programming. Universities educate kindergarten to grade 12 (K–12) teachers, but opportunities for pre-service teachers to learn about ESL issues are ad hoc. School boards determine how ESL is delivered across districts, but they face severe funding constraints in the current economic climate. If students are coded as ESL, their schools receive supplementary funding to provide language instruction; however, many needs are not met, and this contributes to high dropout rates. Several nongovernmental organizations have established out-of-school homework clubs to provide additional support. These well-intentioned efforts rely heavily on volunteers, only some of whom have the necessary skills. ESL parents are sometimes distraught because they perceive that their children are not receiving a good education. Although most stakeholders are sincere in their commitment to support immigrant children and youth, the lack of systematicity and coordination has resulted in terrible human costs. We make recommendations (including, for example, assessment, professional development for school staff, and elimination of the age cap) for providing these students with an equitable education.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.191 | 0.048 |
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".