Bibliographic record
Abstract
In August 2013, the Eastern Ontario Warden’s Caucus (EOWC) produced a series of whitepapers that address municipal affordability in Eastern Ontario and the financial sustainability of local governments. With costs drastically outpacing population growth, rural municipalities have few means to bridge the gap. The white papers report that municipal operating budgets have increased by 65% over a ten year period, while population growth rose 13%. The factors driving costs are the same for each municipality, which supports the need to increase efficiencies through a regional approach on cost sharing. This same approach needs to be considered in economic development as communities continue to compete for investment from the same market place.This paper proposes that regional collaboration will result in economic sustainability. Economic and municipal strategies need to reinforce collaborative strategies through the development of a regional approach that shares costs and secures partnerships to deliver services and contain these costs. Short term actions should include developing an economic development strategy for Eastern Ontario, securing funding for infrastructure maintenance, and forming a task force that will investigate ways to contain infrastructure costs.Keywords: Collaboration, economy, regional, sustainability, growth
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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.020 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".