Is the Union Employment Suppression Effect Diminishing? Further Evidence from Canada
Bibliographic record
Abstract
That unions suppress employment growth among their employers has been such a ubiquitous finding that it has been dubbed “the one constant” in industrial relations research (Addison and Belfield, 2004). However, all of the empirical findings on which this conclusion is based come from data collected in 1998 or earlier, and the Canadian findings (Long, 1993) date from more than twenty-five years ago. Noting this, Walsworth (2010a) utilized data from the Statistics Canada Workplace and Employee Survey (WES) covering the period 1999-2005 to investigate the more recent magnitude of the employment growth suppression effect in Canada. He found that, compared to Long’s (1993) findings, the union employment suppression effect has apparently diminished in Canada. However, we note that Walsworth’s (2010a) analysis is not comparable to that conducted by Long (1993) in several ways. For example, Walsworth (2010a) did not segment his analysis by establishment size, or by industrial sector.Moreover, Walsworth (2010a) attempted no analysis of the reasons behind a possible diminution in the union employment growth suppression effect, an omission that we address by examining employee earnings growth and the union wage premium as possible contributing factors. We analyze WES data collected during 2001-2006 and, like Long (1993), find important differences when segmenting our analysis according to establishment size, as the union employment suppression effect was evidenced in large manufacturing establishments, but not in smaller manufacturing establishments. However, unlike Long (1993), we also find important differences between the manufacturing sector and the service sector, where we find no union employment suppression effect among larger service establishments, and a significant positive union effect on employment growth among smaller service establishments — the first finding of a positive union employment growth effect in any context. Our analysis suggests that a declining union wage premium may have played a role in these results.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".