The Impact of Occupational Role on the Burnout Level Experienced by Higher Education Professionals
Bibliographic record
Abstract
The purpose of this study was to identify whether there is a difference in the average levels of burnout, as defined by Maslach and Jackson’s (1981) three-factor model, experienced by higher education staff members depending on their occupational role or job title. This investigation responded to the problem of increasing levels of stress and burnout experienced by individuals working in the higher education sector (Poalses & Bezuidenhout, 2018) by contributing further information about which professionals are at highest risk of burnout. This study was conducted using a quantitative methodology and a causal-comparative, survey-based research design. The target population of this project was staff members (teaching, non-teaching, and administrative professionals) working in higher education institutions in Greater Vancouver, Canada. Nonprobability convenience sampling was used to select participants who were willing and available to participate. To assess whether staff members with different occupational roles experienced different levels of the three subdimensions of burnout (emotional exhaustion, depersonalization, and reduced personal accomplishment), a quantitative survey was presented online via SurveyMonkey; this consisted of demographic questions and the Maslach Burnout Inventory-Educators Survey (MBI-ES) (Maslach & Jackson, 1986). The resulting quantitative data was analyzed using the Kruskal-Wallis ANOVA, and it was found that professionals working in different occupational roles experienced significantly different levels of personal accomplishment. Burnout scores in the areas of emotional exhaustion and depersonalization also varied significantly depending on whether or not participants held their preferred employment status. Lastly, analysis revealed that there was a statistically significant difference in emotional exhaustion scores depending on participants’ sexual orientation. Identifying the relationship between burnout and occupational role is intended to help leaders of higher education institutions recognize which professionals are at highest risk of burnout, so that effective support and resources can be provided to those who need them.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".