Do Unions Still Matter for Redistribution? Evidence from Canada’s Provinces
Bibliographic record
Abstract
We examine the relationship between union power and redistribution in Canada’s ten provinces between 1986 and 2014. Subnational jurisdictions are thus the focus of research questions that have previously been addressed at the international level. Multilevel models with time-series cross-sectional data are used to estimate the long-term association between union density and redistribution through provincial transfer payments and income taxes. We found that higher union density correlates with considerably more redistribution over the long term but not over the short term. This finding is confirmed by three distinct measures of inequality and poverty reduction, an indication that it is quite robust. The association is significant for the entire study period and for its second half. This finding is consistent with power resource theory in its original form, but not with more recent work in that area or with comparative political economy scholarship, which generally now neglects or downplays the impact of organized labour on social and economic policy outcomes. Our findings suggest a need to re-assess the diminished interest of recent researchers in the political influence of organized labour. It will also interest scholars in other countries where tax and transfer systems are decentralized, and where the impact of organized labour on such measures has been understudied at the subnational level. Additionally, we show that unionized voters in Canada are more favourably disposed than their non-unionized counterparts toward redistribution and toward pro-redistribution political parties. Unions may consequently affect redistribution in part by socializing their members to favour it. This possibility is advanced with preliminary data in this paper. We argue that further scholarly attention is both required and deserved on this subject in Canada and elsewhere.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".