The BC Settlement Collaborative Case Management Service Model : Baseline Report
Bibliographic record
Abstract
Case management has become a crucial component and practice of settlement service in Canada to serve newcomers with high and complex needs. So far, systematic evaluation of this practice model in settlement service has not yet been done. Led by MOSAIC, the Innovative BC Settlement Case Management Service Model (SDI) aims to examine the existing settlement case management interventions and produce an evidence and outcome-based settlement case management service model. The project has three sequential phases: 1) establish the baseline understanding of existing case management services, 2) develop a Collaborative Case Management Model (hereafter Collaborative Model), and 3) test the outcome of the Collaborative Model.The final report of the project, The BC Settlement Collaborative Case Management Service Model Final Report, is also accessible through cIRcle: http://hdl.handle.net/2429/89293.
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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 | 0.062 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.009 |
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".