Bibliographic record
Abstract
The present research aims to study effectiveness of Shafi Abadi's multi-axial pattern on reducing occupational burnout of primary school teachers in District One of Tehran.Research's statistical population includes 100 number of teachers at primary stage in District One of Tehran from which 30 number were selected as sample volume following performing relevant tests.This was a semiexperimental study with pre-test and post-test design with control group.This research's statistical population consisted of 100 number of primary school teachers in District One of Tehran from which 30 teachers were selected by simple random sampling method.Selected teachers were randomly replaced at research's different condition (experiment group= 15 persons and control group=15 persons).Experiment group participated in Shafi Abadi's multi-axial training pattern plan following performing pre-test for both groups, but no training plan was applied for control group and post-test for both groups was applied at last session.So, findings required for evaluating research issue were collected and they were analyzed by software SPSS and Covariance test.Covariance analysis showed that teaching Shafi Abadi's multiaxial pattern influences all the occupational burnout's components and teachers' occupational burnout can be reduced through this pattern.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.833 | 0.729 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".