Comparing Public and Private Compensation in British Columbia
Bibliographic record
Abstract
As British Columbia’s provincial government continues to struggle with both deficits and finding ways to constrain spending, there is heightened interest in how wages and non-wage benefits (compensation) in the public sector compare with those in the private sector. While a lack of non-wage benefits data mean that there is insufficient information to make a definitive statement about total compensation between the private and public sectors, the data that are available indicate that the public sector enjoys a clear wage premium. There are also strong indications that the public sector has more generous non-wage benefits than the private sector. After controlling for such factors as gender, age, marital status, education, tenure, size of firm, type of job, and industry, public sector workers (including federal, provincial, and local) located in British Columbia in April 2011 enjoyed, on average, a 13.6 percent wage premium over their private sector counterparts. When unionization is factored in, the premium is reduced to 11.2 percent. As of 2011, 89.8 percent of public sector workers in British Columbia were covered by a registered pension compared to 19.4 percent of private sector workers. In addition, 95.6 percent of British Columbia’s public sector workers who were covered by a pension enjoyed a defined benefit pension plan compared to 49.3 percent of private sector workers. In 2011, job losses were greater in B.C.’s private sector than in the public sector: 4.3 percent of private sector workers lost their jobs compared to 0.6 percent of public sector workers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".