Immigration and Rural Canada: Research and Practice \n(Final Report)
Bibliographic record
Abstract
The Canadian Rural Revitalization Foundation (CRRF) and Rural Development Institute (RDI) partnered in delivering National Rural Think Tank 2005- Immigration and Rural Canada: Research and Practice, which was held in Brandon, Manitoba on April 28. The event drew fifty invited participants representing the areas of policy, research and community from across Canada. Western Economic Diversification Canada (WD), Manitoba Labour and Immigration (LIM), New Rural Economy (NRE), Atlantic Canada Opportunities Agency (ACOA), CRRF’s National Rural Research Network (NRRN), Rural Secretariat and Citizenship and Immigration Canada (CIC) provided financial support for the event. \nObjectives of the Think Tank included: to identify and clarify the pertinent issues surrounding rural immigration policy, research and practice; to inform participants of the existing policy and opportunities surrounding rural immigration within the framework of “the present rural reality”; to connect the perspectives of research, policy and application by engaging interests, opinion and expertise from broad fields; to provide an opportunity for networking, facilitating future follow up on the theme; to mobilize people and ideas towards a national rural immigration agenda; and to promote active participation and contributions from all in attendance.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.012 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.036 | 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".