Making Fort McMurray Home: Space and Place on Canada’s New Frontier of Oil Production
Bibliographic record
Abstract
Since the beginning of the 21st century, the city of Fort McMurray, in northern Alberta, has welcomed tens of thousands of newcomers attracted by the high salaries of a booming oil sands industry. In this context, one of the major challenges faced by the municipality and the companies is to retain employees and their families so as to build a sustainable community. In this paper, we will take a closer look at the way this challenge is being met, first by considering how humanistic geographers such as Yi-Fu Tuan and Edward Relph have defined the concepts of space and place so as to elaborate on this idea of “making Fort McMurray home.” Then, relying on field work conducted in October 2014, we will attempt to underline the different approaches the municipality and the oil sands companies have followed to frame the identity of Fort McMurray and promote identification with it. Finally, we will look into the part the non-profit sector plays in fostering a sense of place in this boom town.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.012 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".