Does a Specific Union Impact on Wage Increases? Evidence from Canada, 1985-2007
Bibliographic record
Abstract
The purpose of this note is to examine the effect of belonging to a specific union on negotiated wage increases, given unionisation status. The data consist of all collective agreements with more than 500 employees, which were signed in Quebec (N=632) or Ontario (N=1349) during the 1985-2007 period. The model used is a standard wage equation with the negotiated rate of increase of base wages, annualized as the dependent variable and four dichotomous variables for a specific union, the CPI and the unemployment rate two quarters before the collective agreements, the presence or not of a cost of living agreements in the collective agreement and eighteen industrial dichotomous variables. We find with one exception no evidence that one union is better than another in obtaining higher wage growth. L'objectif de ce cahier est d'examiner l'impact d'une affiliation syndicale spécifique sur l'augmentation des salaires négociés, étant donné la syndicalisation. Les données sont l'ensemble des conventions collectives de 500 employés et plus qui ont été signées au Québec (N=632) et en Ontario (N=1349) durant la période 1985-2007. Le modèle utilisé est une équation salariale typique avec le taux d'augmentation salariale annualisé comme variable dépendante et quatre variables dichotomiques pour les syndicats spécifiques, l'IPC et le taux de chômage retardée de deux périodes par rapport à la signature, la présence ou non d'une clause d'ajustement au coût de la vie et 18 variables de secteur industriel. Nous ne trouvons sauf pour une exception aucun résultat indiquant qu'un syndicat obtient des augmentations plus élevées qu'un autre.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".