Barriers to Sustainable Economic Development for a Middle-Sized City in Western Province of Newfoundland and Labrador, Canada
Bibliographic record
Abstract
The United Nations Sustainable Development Goals (SDGs) set the criteria for sustainable economic development. These goals encompass four dimensions, including social, human, economic, and environment, of which the last two goals (i.e., economic and environment) were contemplated in this study. A case study for Corner Brook, a middle-sized city, located in the western region of the province of Newfoundland and Labrador, Canada, revealed that the current urban water use pricing mechanism is not matched with the SDGs, which reflects impediments to the city’s achievements to become a sustainable economic development community. Residents are billed a fixed rate for water use rather than a tiered or usage-based rate. This is not a resilient policy, as it fails to conserve water resources, ultimately leading to wasting freshwater produce, inhibiting economic growth, creating social exclusion, and degrading natural resources. We recommend changing the current flat-rate based water billing mechanism to either increasing block tariffs or two-part tariffs, adjusted by seasonal rates; issuing governmental policies, such as rebates, subsidies, and lower property taxes to entice residents’ willingness-to-install water meters on their premises; encouraging provisions such as using rain barrels to help cut down water consumption; and raising public knowledge through social media on how high per capita water use is in the region, including how much it costs to install water meters. These recommendations will also help provincial and municipal policymakers pursue the SDGs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".