Facilitating workforce development: The economic developer’s role in supporting economic stability in medium and small resource-based British Columbian cities
Bibliographic record
Abstract
The availability of a talented workforce is increasingly being cited as a barrier to growth by businesses across Canada. This worker shortage is particularly challenging for organizations looking to expand in medium and small resource-based cities. This is due to an increase in outmigration to large cities by people seeking knowledge economy based employment and negative perceptions of resource-based cities. These factors hinder employer’s ability to attract people to their smaller resource-reliant communities from other cities. Economic developers in these smaller cities can adjust to these changing realities by highlighting their community’s strengths in relation to larger cities to attract and retain the skilled talent needed to support the growth of their existing businesses and to attract new business. Economic developers in the Kootenays, Prince George and Quesnel have all recognized this opportunity and the work being done in these communities to increase the population base can be used as a model by other communities grappling with similar workforce attraction and retention issues. Keywords: economic development, workforce, population, attraction and retention, natural resources, urbanization, outmigration
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".