Employee Retention for Economic Stabilization: A Qualitative Phenomenological Study in the Hospitality Sector
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Focusing on employee retention is vital to increase organizational performance and strengthen a nation's economy. Employee turnover leads to high unemployment and slow economic growth around the globe. The purpose of this study was to explore the reasons and motivating factors that cause employees to remain in hospitality despite the high turnover rate in the industry. The data for this study were collected using semi-structured interviews, conducted with hospitality employees in South Florida. The study employed a qualitative phenomenological method to acquire the lived experiences of participants. The findings were in accord with the employee retention approach. The findings revealed that creating a good working environment including management support, reward, and incentive programs would lead to employee retention in the hospitality sector.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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