Research on the Satisfaction Degree of Basic Level Employees in Chain Hotels —— Take Jinan Rujia Chain Hotel as an Example
Bibliographic record
Abstract
In recent years, there is a common problem in hotels. The turnover of grass-roots staffs is frequent and the turnover rate of staffs is high. This paper takes Jinan Rujia Chain Hotel as an example, designing a questionnaire to investigate the satisfaction of the grass-roots employees of Rujia Hotel. The principal component analysis of the data obtained from the survey was carried out by using SPSS analysis tools, then the conclusions were drawn as follows: The overall satisfaction of the grassroots staff of Rujia Hotel in Jinan is not very high. Among the five main factors, the employee satisfaction of the job treatment factor is the highest, while the interpersonal relationship factor is the lowest, which is only 0.0373. Personal development factor is second only to interpersonal relationship factor, employee satisfaction is 0.0482, but on the whole, the employee satisfaction of the five main factors is low.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".