Canadian Federation of Independent Business 1 Wage Watch A Comparison of Public-Sector and Private-Sector Wages
Bibliographic record
Abstract
Public sector employees continue to benefit from higher wages and non-wage benefits relative to their private sector counterparts. Coupled with the large increase in public sector employment in recent years, such wage premiums exert pressure on government expenditures and can eliminate any benefits obtained from tight fiscal management in the 1990s. Moreover, wage premiums distort local labour markets as public and private employers compete to attract and retain skilled workers. This study re-examines wage disparities between private-sector employees and those in public administration at the federal, provincial, and municipal levels. Updating CFIB’s previous research, the study compares wages among occupations that are only found in both public administration and the private sector. Using Census data the study finds that, at all levels of government, wage premiums persist in favour of public administration (see Figure 1). Moreover, a significant overall increase in the wage premium favouring federal employees, over the 1995-2000 period, is found; while the premium enjoyed by provincial employees decreased and the premium paid to municipal employees remained relatively constant over the same period. Non-wage benefits such as employer pension contributions, premiums on disability, life, and medical insurance, are examined on a national aggregate level. Although non-wage benefits, as a percentage of wages, declined in public administration employment, they remain, on average, 60 per cent higher than those of private sector employees. These benefits significantly increase the total compensation premium enjoyed by employees in public administration.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.105 | 0.017 |
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".