<scp>D</scp>oes <scp>N</scp>on‐Union <scp>E</scp>mployee <scp>R</scp>epresentation <scp>A</scp>ct as a <scp>C</scp>omplement or <scp>S</scp>ubstitute to <scp>U</scp>nion <scp>V</scp>oice? <scp>E</scp>vidence from <scp>C</scp>anada and the <scp>U</scp>nited <scp>S</scp>tates
Bibliographic record
Abstract
This paper examines two central questions related to non‐union employee representation ( NER ) in Canada and the United States. First, using Taras and Kaufman's (2006) four faces NER approach, we ask whether non‐union and union forms of voice act as substitutes or complements for employees at the workplace? Second, we ask whether non‐union forms of employee representation serve to deflect any latent desire for traditional union voice. We find that NER is negatively related to the presence of unionization at the workplace; it appears to reduce the desire to be unionized. This substitution effect proves to be stronger in Canada than in the United States.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.154 |
| Meta-epidemiology (narrow) | 0.011 | 0.011 |
| Meta-epidemiology (broad) | 0.012 | 0.008 |
| Bibliometrics | 0.007 | 0.015 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.013 | 0.006 |
| Research integrity | 0.010 | 0.018 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; both teacher heads agree on what is shown here.
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".