Attitudes towards Faculty Unions and Collective Bargaining in American and Canadian Universities
Bibliographic record
Abstract
This study analyzes attitudes towards faculty unions and collective bargaining among faculty and administrators in the United States and Canada. This is the first study which compares support for unionization and collective bargaining in American and Canadian universities among faculty members and administrators. The main research question is: Which factors are the determinants of attitudes towards faculty unions and collective bargaining in American and Canadian universities and colleges? Our hypotheses are that cultural, institutional, political, positional, socio-economic, and academic factors are significant predictors of support for faculty unionization. The academics in Canada are likely to be more supportive of faculty unionism compared to their American counterparts because of differences in national political cultures. Institutional and political factors are also likely to affect such views. This study uses comparative and regression analyses of data from the 1999 North American Academic Study Survey to examine attitudes towards unions and collective bargaining among faculty and administrators in the United States and Canada. The analysis shows that Canadian academics are more supportive of faculty unions and collective bargaining than their American counterparts. These results provide support to the political culture hypothesis. However, the study shows that institutional, political, positional, socio-economic and academic factors are also important in many cases. A faculty bargaining agent on campus is positively associated with favorable views of faculty unions and collective bargaining among American professors and with administrators’ support for collective bargaining in both countries. Administrators’ opposition is also important, in particular, for attitudes of Canadian faculty. Professors are more pro-union than administrators in both countries. Income, gender, race, age, religion, and academic field, are significant determinants of attitudes of faculty and administrators in the US and Canada in certain cases.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".