The rhythm of making cheaps: a case study of rhythmanalysis and qualitative labour shortages in Canadian fisheries
Bibliographic record
Abstract
This paper explores how an intersectional rhythmanalysis approach that includes attention to animals, ecosystems and corporate capital investment strategies can provide crucial insight into reported labour shortages. This paper unpacks the systemic relations of difference and power among mobile workers by highlighting the reorganization of temporal rhythms of work and life, but also animals and environments, that work to create or reproduce immobility and enclosure. Drawing on interview data and document analysis related to the seafood processing sector, the paper argues that the construction of qualitative labour shortages is tied to racialized, gendered and classed workers who are migrant or mobile. Critically, this includes new rhythms of capital accumulation, and related arrhythmias in the work/home lives of local and interprovincial migrant Canadian workers, through changes to schedules and seasonal contracts. These rhythmic changes make employment in these plants less desirable or feasible for these workers and support employers’ claims of labour shortages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".