Contractors or Disguised Employees? A Case Study of Couriers in Winnipeg
Bibliographic record
Abstract
The courier industry in Canada is rapidly expanding. This is due to a number of factors including greater international trade in goods; more use of just-in-time inventory strategies; and the rapid development of internet commerce. Significant technological and organizational developments within the industry have led to greater segmentation of markets. As a result, large national and international parcel delivery firms dominate the international and intercity markets, while there has been a proliferation of smaller firms in the same-city, same-day markets. The research findings from a case study conducted in Winnipeg reveal that couriers in certain parts of the industry are relatively well paid, with benefits and employment conditions negotiated by their union, while others are independent contractors with low incomes, no benefits and insecure tenure. The article compares the experience of these two types of couriers and examines what is being done to improve the terms and conditions of work for same-day couriers. It is concluded that nature of the same day courier industry means that union organizing will be very difficult and there is no guarantee of success. Unionization, however, is a necessary prerequisite for the improvement of conditions and wages in this growing industry.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".