A Critical Examination of Enablers and Constraints of Employee Involvement in a Unionised Canadian Higher Education Environment
Bibliographic record
Abstract
The overall purpose of this research is to study the factors that account for the success and failure of employee involvement initiatives with respect to unionised faculty in higher education institutions. Typically, research in High Involvement Work Systems (HIWS) has focused on manufacturing and nonacademic, nonunion service industries. The study sought to fill in the gap in the research on the prevalence of, and requirements for, successful implementation of employee involvement initiatives in unionised, higher education, academic environments. Unlike many existing studies on HIWS that have mainly focused on examining the central research question from either a management or a union perspective, this study examines the faculty perspective with a view to better understanding the factors that promote and constrain faculty’s involvement in their jobs and in the broader organisation. The results could provide key input into policy decisions and into the design of practical interventions that could serve to promote the adoption of HIWS in higher education institutions. Accordingly, the central research question is “What are the factors that account for the success and failure of employee involvement initiatives with respect to faculty in unionised organisations in higher education?” The study was conducted in a large community college in Toronto, Canada, among unionised faculty across a broad range of disciplines.For the purposes of this study, a synthesised employee involvement construct was developed from existing models and theories.This construct was the basis for the design of the initial interviews that formed the basis of the qualitative study portion of this research project as well as for the quantitative survey portion that followed up on the results of the initial interviews.In the qualitative study, a semi-structured interview questionnaire was developed and used to interview 22 faculty members across 6 major departments of the college who were selected by a purposive sampling technique.Data from the interviews were analysed using themes and content analysis and the results were then used to design a survey to explore in more depth the key themes that were identified.The survey comprised 54 questions divided into 8 sections. These questions served to provide a comprehensive understanding of participants’ attitudes using a 5-point Likert scale.The data wereanalysed using SPSS, and descriptive statistics, frequencies, and visual charts were produced to analyse each variable within the sample. From a theory perspective, the results of the study support the current knowledge on the factors that promote and constrain employee involvement generally across a variety of organisations in keeping with current models of involvement, but also extend the literature by identifying additional factors that apply to white-collar, unionised, higher education institutions.These factors include the need for more intrinsic rather than extrinsic rewards, the need for managers to use supportive rather than directive approaches to management, and the importance of using small team-based work groups for information-sharing and problem-solving. Key factors constraining faculty involvement include the existence of a collective agreement that limits faculty autonomy and top-down decision-making and communication channels used by management. This study also has implications for practice regarding creating a high-involvement culture for faculty in higher education institutions. Key among these are ensuring that recruitment and selection procedures identify managers who have the requisite skills and personalities required for supportive management and training managers in the application of these management techniques. Developmental opportunities for faculty in higher education pursuits would serve to provide them with intrinsic rewards. In addition, such opportunitiess would fulfil the objectives of higher education institutions in upgrading the credentials and skills of their faculty to meet government requirements and the competitive challenges facing these organisations. Training for managers, faculty, and union stewards in change management processes is another key requirement for the successful implementation of employee involvement initiatives in the higher education environment.
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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 | 0.014 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".