Job Satisfaction among Academicians at Business Colleges Operating in Kuwait
Bibliographic record
Abstract
The purpose of this study is to examine the overall level of job satisfaction of the academicians who work for business colleges operating in Kuwait and to identify whether demographics affect the level of job satisfaction.During the period between December 2016 and March 2017, a short-form Minnesota Satisfaction Questionnaire (MSQ) was distributed to 240 academicians working for eight Kuwaiti business colleges including: Arab Open University (AOU), American University of Kuwait (AUK), Gulf University for Science and Technology (GUST), Australian College of Kuwait (ACK), Public Authority for Applied Education and Training (PAAET), Box Hill College (BHC), Kuwait University (KU) and the American University in Middle East (AUME). A total of 141questionnaires were returned; resulting in 59% usable response rate.The study showed that academicians in business colleges operating in Kuwait are relatively job satisfied and their characteristics impact the level of their satisfaction. However, the most significant characteristics that affect the level of their job satisfaction were income, nationality and gender.The outcome of this study can be used by policy makers to develop recruitment and promotion policies. This would assist in achieving high levels of job satisfaction and will have positive effect on the academic process and the higher education system at large. This is the first study that used MSQ to explore job satisfaction among academicians who work for eight business colleges in Kuwait. The outcome of the study is expected to help decision makers in enhancing the level of the academicians' job satisfaction.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".