Dump Truck Destiny: Alberta Oil, “East Coast” Workers, and Attachment to Extraction
Bibliographic record
Abstract
Abstract This paper considers how white, rural, working‐class men come to be seen, by employers and themselves, as a “natural fit” for mobile work in resource extraction. Examining mobility between eastern Canada and the Alberta petroleum industry, I trace longstanding racial, geographical, and gendered explanations of these workers as dependent and averse to work. I draw on interviews with employers, employment counsellors, and mobile workers, and media representations to consider how these narratives function to shape and constrain workers’ political imaginaries and understandings of themselves. The pervasive story of these workers as undeserving has enabled the emergence of a contrasting working subject: the hard‐working, flexible “east coast” worker who is a natural fit for mobile work in resource extraction. I argue that, despite the challenges of mobile resource work, the interplay of stories that pathologise and celebrate these workers has encouraged their attachment to resource extraction as the pathway to a better life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".