Análisis de la rotación del personal de la empresa Corporación Mía Internacional SAC - San Luis 2018
Bibliographic record
Abstract
ABSTRACT \nStaff rotation is present in all organizations, the purpose of this thesis is to analyze, determine the rotation of the employees of the company Mia International SAC - San Luis 2018, the research is quantitative descriptive type, the population is made up of 120 employees where 40 employees are those who resigned until the third quarter of the year and 80 active employees within the organization where it was constituted by 53 women and 85 men. For the data collection of the "staff rotation questionnaire", elaborated by (Crisostomo Olivares, J. 2015), the validity was determined by the expert judgment and the reliability with the Alpha coefficient of Cron Bach (, 866 ) the data collected were tabulated, where 100% of employees 22% are satisfied with respect to remuneration as workloads, review of corporate benefits, while 51% are unsatisfied with respect to opportunity, adaptability, leadership said results is analyzed in reference to the perception of the employees where they will allow the company to make decisions to improve the high turnover that occurs, of not taking into account the results this will lead to the reduction of production generating economic losses to the company .
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".