A scan of community economic development organizations, rural communities and First Nations in Manitoba and their participation in the New Economy
Bibliographic record
Abstract
The growth of the New Economy has the potential to positively benefit community economic development (CED) organizations, rural communities and First Nations in Manitoba. Organizations and communities have not necessarily profited equally from this knowledge-based economy. This study sought to identify current participation in the New Economy and how increased participation can enhance CED organizations, rural communities and First Nations. Questionnaires were sent to CED organizations to determine what types of technology they use, how they use it and how it is shared with their community. Rural communities and northern First Nations also received questionnaires, which determined the types and quality of telecommunications in their communities, as well as how technology is used in their local education system. Urban and rural CED organizations are active participants in the New Economy. Technology is integral to all of their activities, and is shared with the community through public access computers. The greatest barrier for CED organizations to participate in the New Economy is the cost of technology. Recommendations for CED organizations included the need to utilize new software for CED planning, to participate in other New Economy activities, to share information with other organizations and to provide a greater number of public access computers for their communities. Participation in the New Economy is very important to rural Manitoba communities for the sharing and dissemination of information and for education and training. The lack of Broadband Internet access in rural communities was identified as their greatest barrier. The need to connect all rural communities to Broadband Internet, to use technology for CED planning, to get local retailers and governments on-line and to provide more public access computers were all recommended for rural communities. Northern Manitoba First Nations have the poorest participation in the New Economy of all respondents to this project. There are still First Nations in northern Manitoba that do not have Internet access. Unreliable Internet connections, a lack of Broadband Internet and inadequate technology are all ongoing problems for northern First Nations. Recommendations included the need to partner with Nations Sphere to access Broadband Internet in all northern First Nations, to use technology for CED planning, to get local retailers and governments on-line, to provide public access computers and to integrate technology into the education system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".