The union and non-union wage differential in the New Zealand public service
Bibliographic record
Abstract
What do unions do? The major objective of unions is to improve the terms of conditions of employment for their members. At the same time, unions have a considerable impact on the employment conditions of not only their own members but non-unionised workers as well. One of the most important employment terms unions negotiate is wages. As a result, wage bargaining has been identified as a primary function of unions, and differences in wages between union and non-union members are considered an important measure of union power. In most countries this differential is called the ‘union/non-union’ wage differential. In New Zealand, however, there are employees who are union members but are not covered by collective agreements, contrary to the more common occurrence in other countries (e.g. the United States and Canada), where non-union members are often covered by collective agreements. Therefore, in New Zealand the differential should be more precisely called the ‘collective versus individual’ wage differential. In this article we focus on the raw ‘collective’ wage differential, but due to convention we still call it the ‘union’ wage differential.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".