WHAT INFLUENCES JOB SATISFACTION IN THE NEW NORMAL? INSIGHTS FROM EDUCATORS OF INDUSTRIAL TECHNOLOGY UNIT/COLLEGE IN A STATE UNIVERSITY
Bibliographic record
Abstract
Abstract This study on job satisfaction among educators in an Industrial Technology Unit/College of a State University in the new normal education setting was a descriptive research; conducted during the first quarter year 2024 among instructors and professors. This study showed that majority of the respondents are male, Master’s degree holder, and teaching in the University for less than two decade as Instructor 1. This study utilized the Job Satisfaction Survey (JSS) of Paul E. Spector (1985) with nine facet scale to assess employee attitudes about the job satisfaction. The instructor/professor-respondents strongly agreed that the Nature of Work was strongly approved aspect/facet of job satisfaction. The respondents find enjoyment in what they are doing (teaching and other services), hence their actions and practices manifest commitment, dedication and satisfaction. The job satisfaction of the instructors/professors was also contributed by facets Supervision, Coworkers and Communication. The findings clearly shows that the social aspects of the facets of the JS survey (Spector, 1985) were more emphasized and valued by the respondents and influenced their satisfaction in their respective tasks, teaching loads and other endeavors in the university such as research, extension, production and other projects and activities.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".