From Kitimat to Tumbler Ridge: A Crucial Lesson Not Learned in Resource-Town Planning
Bibliographic record
Abstract
Resource dependent towns have been a part of the west-ern Canadian urban landscape for more than a century. From Hussar to Hudsons Hope, and from Peace River to Gold River, in many cases these towns were devel-oped by a single firm or industry to provide a focal point for local extraction and processing operations, as well as to house the needed workforce. But why do so many post-World War II resource towns share such similar townsite plans? And, why have they almost always faced similar forms of economic devastation? Despite considerable attention to “best practices ” in town plan-ning and development, even the newest of these towns face familiar concerns over booms and busts and ongo-ing economic vulnerability. This paper draws especially upon the case of Kitimat, BC and compares it to such later resource towns as Mackenzie and Tumbler Ridge. The purpose is to identify which of the early planning lessons have been forgotten and whether this may have some explanatory value in why “crisis ” remains the watchword of so many such towns.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".