Bibliographic record
Abstract
As a result of the recession in 2008, many employers are looking for ways to cut labour costs. One way of doing so is to impose two-tier compensation schemes where older and younger employees do essentially the same job for different wages and benefits. The key concern of this paper is how Canadian labour, employment, and human rights legal regimes could respond, if at all, to the differential impact of two-tier schemes on younger workers. In Part I of the paper, the author recounts the use of two-tier systems in the United States and Canada. He shows that their use not only affects workers’ wages, but also their benefits and pensions as employers move from defined benefit to defined contribution plans. In Part II, he analyzes arbitral, labour board and human rights tribunal case law concluding there are significant barriers to legal recourse for workers in the lower, younger tier through duty of fair representation or human rights complaints. The author ends the paper with an overview of Quebec employment standards legislation, and debates whether similar legislation would be effective in English Canada. He highlights the narrow scope of the Quebec legislation and barriers to enacting a similar statute elsewhere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.017 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".