Labour Productivity and the Distribution of Real Earnings in Canada, 1976 to 2014
Bibliographic record
Abstract
Canadian labour is more productive than ever before, but there is a pervasive sense among Canadians that the living standards of the 'middle class' have been stagnating. Indeed, between 1976 and 2014, median real hourly earnings grew by only 0.09 per cent per year, compared to labour productivity growth of 1.12 per cent per year. We decompose this 1.03 percentage-point growth gap into four components: rising earnings inequality; changes in employer contributions to social insurance programs; rising relative prices for consumer goods, which reduces workers' purchasing power; and a decline in labour's share of aggregate income. Our main result is that rising earnings inequality accounts for half the 1.03 percentagepoint gap, with a decline in labour's income share and a deterioration of labour's purchasing power accounting for the remaining half. Employer social contributions played no role. Further analysis of the inequality component reveals that real wage growth in recent decades has been fastest at the top and at the bottom of the earnings distribution, with relative stagnation in the middle. Our findings are consistent with a 'hollowing out of the middle' story, rather than a 'super-rich pulling away from everyone else' story.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".