A Survey about Teachers’ “Economic Income and Sense of Happiness”of the Sichuan Tibetan Elementary School: Take Ma Erkang County As An Example
Why this work is in the frame
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Bibliographic record
Abstract
The investigation mainly adopts questionnaires and interviews to inquire 120 teachers from Ma Erkang Elementary School in Sichuan Province. The results indicate that the countryside teachers’ income is universally lower than that of urban teachers (teachers from the urban area).Teachers’ sense of happiness of both rural and urban areas is, in general, not optimistic. Countryside teachers’ satisfaction of economic income and sense of happiness is slightly higher than that of urban teachers. Economic income is one of the factors that affect the sense of happiness, yet it is not the most important one. Key words: elementary school teachers; economic income; sense of happinessResume: L'enquete utilise principalement des questionnaires et des entretiens pour enqu 120 enseignants de l'ecole elementaire Ma Erkang dans la province du Sichuan. Les resultats indiquent que les revenus des enseignants dans la campagne sont generalement inferieurs a ceux des enseignants urbains(les enseignants dans les zones urbaines). En general, le sentiment de bonheur des enseignants de zones rurales et urbaines n'est pas optimiste. La satisfaction de revenus economiques et le sentiment de bonheur des enseignants dans la campagne sont legerement superieure a celle des enseignants en milieu urbain. Les revenus economiques est l'un des facteurs qui influent sur le sentiment de bonheur, mais ce n'est pas le facteur le plus important.Mots-Cles: enseignants de l’ecole primaire; revenus economiques; sentiment de bonheur
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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 | 0.004 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it