Urban-Rural Interaction in \nNewfoundland & Labrador: \nSummary of Pilot Region \nQuestionnaire Results
Bibliographic record
Abstract
To better understand the governance mechanisms in the three pilot regions involved in the Rural-Urban Interaction in Newfoundland and Labrador: Understanding and Managing Functional Regions project three types of questionnaires were delivered during the period of July 2008 to spring 2009: one to local businesses, one to local and one to regional non-government organizations (NGOs).Survey results provide insights into the history and mandate of 62 local and regional organizations operating within these regions, as well as their membership, scale of operations, resources, mechanisms of communication and collaboration, governance structures and processes, labour market and sustainability outcomes, key challenges and lessons learned.A total of 70 local businesses also provided perspectives on local labour markets, client service areas, opportunities and challenges.Responding businesses tended to be formed after 2000 and to operate within the service sector.Local NGOs were most likely to address social objectives within their mandates.Economic development was the most common focus for NGOs serving multiple communities (regional NGOs), although social objectives were also pursued.The vast majority of regional NGOs have staff members and annual operating budgets, while most responding organizations that serve single communities (local NGOs) do not.Regional NGOs also tend to have a higher number of volunteers and to have been formed since 1990.Most local and regional NGO respondents
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".