Nonprofit engagement with provincial policy officials: The case of NGO policy voice in Canadian immigrant settlement services
Bibliographic record
Abstract
Abstract This paper explores the role of nonprofit organizations in the immigrant settlement and integration sector in the public policy process in three Canadian provinces. Drawing on thirty one (31) semi-structured interviews with nonprofit and mid-level policy officials (working for a provincial government) in three provinces (Ontario, British Columbia and Saskatchewan), the place of nonprofit agencies in providing input and voice to policy issues in the area of settlement and integration services is presented. Issues regarding the willingness to use advocacy/voice with government funders, the usefulness of government consultations, strategies used in approaching government, the role of research in making evidence-based cases regarding policy and program change, among other considerations are examined. The assessments provided by key nonprofit actors and government policy officials are used to bring better understanding of the perceived roles of nonprofit organizations in the daily work of policy.
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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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.072 | 0.021 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".