Challenges of community development corporations in Rural Manitoba, The
Bibliographic record
Abstract
Community Development Corporations (CDCs), as part of a series of Manitoba government initiatives to develop rural areas through economic development, have acted as vehicles of change within their communities to create solutions. This thesis was undertaken to learn about this rural development effort. The research identified the active CDCs within Manitoba, determined factors that can limit their ability to operate, and identified the activities and functions in which CDCs are engaged. This study provides information on the current conditions and challenges that CDCs encounter. The data was collected through a two-phase method where all municipalities within the Province of Manitoba were asked to identify whether they were associated with a CDC. Once that information was obtained, the principal data collection instrument was utilized to collect detailed information about these organizations. One of the main findings was that the number of active CDCs has decreased over the past decade. The retention and funding of staff is a concern shared with other CDCs across North America. The lack of diversified funding sources was also identified as a key issue. Another theme concerned the operational challenges that are created in light of limited increases in funding. The findings indicated that CDCs undertake a wide range of functions and activities that need to be recognized. The Community Works Loan Program was also examined to assess the success and believed capacity of organizations to manage such a program. This knowledge is valuable for policy and decision makers when determining how they wish to utilize the rural development tool that was created.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".