Concerning labour markets and the commodification of social difference in the Alberta oil sands
Bibliographic record
Abstract
In this thesis, I consider ethnographic conversations I had during fieldwork in Fort McMurray and Edmonton, Alberta, Canada, in 2016 with two sets of workers: Albertan trades-workers employed in the oil sands (pipe-fitters, welders and boilermakers) and Filipino/a Temporary Foreign Workers (TFWs) employed in the local service sector (cooks, caregivers and kitchen helpers). I analyse these workers’ self-reflections on their own work routines as providing a sightline into the ways labour market processes and regulatory frameworks are manifest in and negotiated through their lives. I draw especially on the theories of Karl Polanyi and Karl Marx in my analysis. Through ethnography I also show how the labour market processes these thinkers analyse shape, and are shaped by, social differences they each tend to neglect (e.g. nationality, citizenship, migration status, race, ethnicity, gender), and which more recent post-colonial, feminist, and critical race theorists have emphasised. Hence from the Albertan context, I conceptualise how state-regulated labour markets re-fashion, and are re-fashioned by, the cultural identities of workers. I show how local labour market processes re-make and aggravate social differences between Albertan trades-workers and Filipino/a TFWs in Alberta, in ways that are not superficially or simply motivated by forms of discrimination (e.g. xenophobia, racism, sexism), but which nonetheless agitate and divide an emergent “precariat” (Standing 2011). I hope this thesis can provide the basis for further ethnographic and comparative research.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.075 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".