The call for an evidence-based integrated funding and service delivery system for newcomers
Bibliographic record
Abstract
As immigration continues to drive Canada's growth, the newcomer serving sector remains pivotal in facilitating newcomers' integration into communities. However, this sector grapples with ongoing challenges, exacerbated by the federal government's priority to increase immigration levels, thereby complicating the settlement landscape. This article examines the funding and service delivery difficulties organizations encounter. It underscores a system that fosters funding competition, impedes interorganizational collaboration, complicates program outcome reporting, and entails high administrative costs. Additionally, it addresses the specific challenges faced by newcomer children, youth, and families settling in Canada. The recommendations emphasize that no single agency can resolve the settlement sector crisis alone. Urgent actions include piloting integrated networks over integrated services and adopting a new Immigration, Refugees and Citizenship Canada funding model that aligns with population and cultural needs. Moreover, eliminating silos is essential to establish a cohesive and efficient service delivery network committed to public outcomes and accountability.
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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 | 0.223 | 0.422 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.027 | 0.020 |
| Open science | 0.011 | 0.020 |
| Research integrity | 0.012 | 0.024 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".