Evaluación del sistema de gestión en seguridad y salud en el trabajo de la empresa PROVEFRUT S.A. De la ciudad de Latacunga, Propuesta de un sistema alternativo.
Bibliographic record
Abstract
This Thesis work develops a study for the Implementation of a System of Administration in Security and Occupational Health using the SASST in PROVEFRUT S.A., with this work the company wants to develop a System of Administration to eliminate, and diminish the daily risks. The proposal is an investment for the company, being it economic, viable, current, secure, reliable and efficient for the implementation of a System of Administration in the three levels of Security and Health in any labor environment that is the Human Resource and Technical Administration. The chapters described in this thesis are in function of the System to be implemented having in the first chapter the clear basis that this study pursues to get to the operation of the System of the Security and Health in the Work. The second chapter treats about the SASST model; it was given by Risks of the Work of the IESS contemplating the 3 levels of Administration that should be applied in the Administration for the Security and Health in the Work. In the third chapter is carried out the analysis and the diagnostic of the Security and Health in the plant of PROVEFRUT S.A. to evaluate all the existent risks with the respective Map of Risks, there are recommendations to avoid or to diminish the most outstanding risks in the company, besides in this chapter it is described the sinister that the company used to have such us accidents and occupational illnesses so that there is a yearly comparison and the evolution can be seen when it is implemented. In the quarter chapter the proposal is already made with the whole methodology to be applied in the Administration of the System of the Security and Health in the Work. The way in which all the registrations are taken; the practices that are taken to eliminate or to diminish the risks of the company. The result of this system is taking care of the workers so that they are developed in a sure and healthy atmosphere, with this the companies that applies it will be rewarded in a constant growth and continuous improvement of their production, because a company with responsibility in Security and Health for its workers gives sources of work without risks.
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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 | 0.047 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".