Communication Disorders and the inclusion of newcomer African refugees in rural primary schools of British Columbia, Canada
Bibliographic record
Abstract
In Canadian public primary schools, newcomer West African refugees like other ethnic immigrant students are a visible minority group, often referred as Linguistic and Culturally Different (LCD) students. In the province of British Columbia, newcomer immigrant students are subjected to a battery of tests, as soon as they enroll in the primary public school system. These tests are the provincial Standardized Assessment Tests (SAT) and classroom Teacher Assessment of Learning (TAL) that aim at obtaining data for diagnostic purposes of students‘ learning and teaching purposes. Specific to LCD refugee and immigrant students, they are also assessed on English Language Communication Proficiency (oral and written), Social Skills amongst others, regardless of the degree of proficiency in English language as members of the Anglo-phone Commonwealth countries whose curriculum and medium of instruction is British related. More often, the African immigrants and refugee students of the Anglo-phone African countries are most times diagnosed with English Language Communication Disorders (ELCDs), which has been questioned by some Canadian researchers of Learning Disabilities (LDs) and Multicultural Education (ME), especially with regards to the cultural compatibility of the assessment process/diagnostic tools, and criteria used to assess these LCD refugee and immigrant students. The article discusses the above discourse, with the support of findings of a qualitative ethnographic research findings and related literature
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".