Exploration of Organizational Commitment and Job Satisfaction of Faculty Members in Private Higher Education
Bibliographic record
Abstract
The principal objective of this research is to explore organizational commitment and its effect on job satisfaction styles in a sample of teaching staff working at Alturath University college within the Private Higher Education (PHE) at Baghdad, Iraq. The research sample included 37 faculty members working at different departments. The authors developed a questionnaire with (5-points) Likert scale, and used it as the main instrument to collect data from the sample studied. The questionnaire was subjected to a Cronbach alpha test to verify its internal validity. The statistical package SPSS v.10 was used to analyze and present the data obtained through the questionnaire. The data were also used to test the research hypothesis. According to the responses of the sample members, the statistical tests assisted the research hypothesis which states that there is a significant relationship and effect between organizational commitment and job satisfaction. In addition, the analysis revealed that there is a strong level of organizational commitment among the sample studied. The results obtained by this research can direct the administrations of the college in planning job loads, and in improving organizational commitment. Although this research is limited to one private colleges, but its results add a great value since it provide several lessons that private education can benefit from. This work could, also, be considered as an attempt to increase our knowledge about the educational system in general, and on the PHE in specific.
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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 | 0.004 |
| 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) | 0.002 | 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".