Isap Program Review For Citizenship And Immigration Canada
Bibliographic record
Abstract
Citizenship and Immigration Canada’s Settlement Directorate – Ontario Region (CIC Ontario) hired RealWorld Systems to review its Immigrant Settlement and Adaptation Program (ISAP) in November 2002. The program review focused on the needs and experiences of newcomers to Canada, on the planning, delivery, and evaluation of settlement services in Ontario, and on necessary changes and/or improvements to ISAP. ISAP funds direct services to immigrants and refugees: primarily reception, needs assessment, orientation and information, referral to community resources, interpretation and translation, para-professional counselling, and employment-related services. ISAP also funds indirect services that contribute to improving the delivery of overall settlement services to newcomers, such as research and training. The program review incorporated many different perspectives and activities, including hundreds of interviews and surveys with newcomers, agencies and key informants, as well as several group consultations and a scan of the relevant literature. Our recommendations are based on two assumptions: That newcomers need access to the full range of services that are available to all Canadian residents, and that ISAP funding cannot possibly replace the other service sectors (such as health, employment, education and so on). It is vital that ISAP focus its mandate to ensure that newcomers get the services they need rather than settling for a parallel and under-funded service system. Our five major recommendations, below, aim to improve the effectiveness of ISAP services within the context of the challenges facing the settlement sector as a whole. This upload includes the final report and recommendations as well as the working papers and detailed methodology.
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 | 0.037 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.032 | 0.043 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".