Lifelong Education Strategies and Their Relationship to Achieving Personal Happiness Among Teachers of Al-Kharj Governorate
Bibliographic record
Abstract
This research studies the relationship between lifelong education strategies and achieving personal happiness among teachers of Al-Kharj Governorate. The research used the descriptive, correlational method, and the sample contained teachers, Al-Kharj Governorate- second semester of the academic year 2024. The research linked to the fourth goal of the Sustainable Development Goals 2030 “Quality Education” and its executive objectives cantered on “Education transforms lives”, and the importance of achieving their educational life quality and personal happiness as individuals to meet the labor market requirements in the contemporary industrial revolutions' era. To answer the research questions, the study used two tools prepared by the researchers: a scale of the personal happiness, and a personal interview card to survey opinions on how to achieve personal happiness through lifelong education strategies. The results are expected to show a strong, statistically significant relationship between lifelong education strategies and the degree of achieving personal happiness among teachers of Al-Kharj Governorate. Because it is a major requirement for achieving success in life and achieving personal happiness for the individual and society .
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".