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Record W7110448748 · doi:10.3390/urbansci9120521

Barriers to Sustainable Economic Development for a Middle-Sized City in Western Province of Newfoundland and Labrador, Canada

2025· article· en· W7110448748 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPer capitaSustainable developmentWater resourcesSustainabilityNatural resourceEconomic costWater developmentPublic good

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.242
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it