Planning for growth in a natural resource boomtown: challenges for urban planners in Fort McMurray, Alberta
Bibliographic record
Abstract
Between 2000 and 2010, the population of the city of Fort McMurray, Alberta increased by 80%, mainly due to the expansion of oil extraction projects and subsidiary industries. Population growth of this magnitude has significant consequences for city planning. While Fort McMurray struggles to keep up with enormous numbers of in-migrants, the cost of living in the city has skyrocketed. Using interviews with city planners and field experience in the city, in this paper I examine the current challenges faced by urban planners in Fort McMurray against the backdrop of global economic decision-making, corporate influence, and commodity dynamics. While the recession of 2008 gave city planners some breathing room, they still struggle with gathering accurate census information and predicting population growth, providing affordable housing, and balancing short-range planning with their long-term goals. Attempts by city planners to address these challenges could provide a contemporary model for urban planning in rapidly growing, resource-dependent communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".