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Edmonton, a resource city: urban development examined through unrecognized resource legacies

2025· article· en· W4413407270 on OpenAlexaboutno aff
Peter Whyte, Kristof Van Assche

Bibliographic record

VenueResources Policy · 2025
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsResource (disambiguation)Environmental planningResource useNatural resource economicsBusinessGeographyEconomicsComputer science

Abstract

fetched live from OpenAlex

Edmonton, Alberta, is currently associated with oil and gas industries, yet its history as a resource community is in many ways not only obscure but also influential, even key to the understanding of its urban development. Timber harvesting, brick making but most importantly local coal mining powered and structured Edmonton's growth. Several communities were key to this foundation, ultimately becoming hosts for many other city sustaining functions. River flats communities like Riverdale and Cloverdale were vulnerable to floods. Beverly, an official coal mining town had a prolonged history of struggle. McCauley was home to the Federal prison; resident prisoners mined the coal beneath Riverdale. Coal mining in Edmonton was replaced by informal and social housing, waste management, major transportation projects, and finally development of Edmonton's River Valley parks system. Edmonton provides a case study for expanding the resource communities narrative. Key communities in Edmonton's early years show how coal mining influenced landscape, economic shifts, and relationships within a growing city. A combined process of GIS analysis, local media analysis, and literature review provides a framework for understanding how Edmonton, a large northern city initially shared the experiences and difficulties of small resource communities in earlier years of growth and development. Large and diverse cities which seemingly transcended their extractive origin can be analyzed through the lens of resource legacies, which can reveal, as in Edmonton, that largely forgotten histories of vanished resources can mark cities and their planning in profound ways. We therefore speak of opaque resource cities.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.545
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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