Relations Between School and Immigrant Families in Albertan Francophone School: Perspectives of Settlement Workers in Schools — A Secondary Publication
Bibliographic record
Abstract
In recent years, Francophone schools in Alberta, a province in western Canada, have seen significant ethnocultural diversification of their school population, thus reflecting recent migratory changes in Canada. The population of a Francophone school board located in an agglomeration of Alberta reflects these new migratory trends. A partial ethnodemographic portrait carried out in 2003 in six of its schools indicates that 50% of the pupils come from an immigrant background and come from 23 different countries; mostly from sub-Saharan African countries. This demographic reality, confirmed more than a decade later, represents a major structural change for Francophone schools. In Alberta, as in other Canadian provinces, inclusion is at the heart of discourse and educational practices. With a transformative aim, it intends to promote ethnocultural diversity in the classroom and equal opportunities through school equity practices. This article focuses on the settlement workers in schools responsible for bridging family, community, and school cultures. The analysis of the interviews of the four workers sheds light on and questions both the institutional practices and the personal strategies put in place to face the challenges encountered in this tripartite collaboration.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.049 | 0.016 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".