Estudio de medición del trabajo en Holguín y su influencia en el desarrollo del territorio
Bibliographic record
Abstract
The present investigation constitutes a sample of the advances that have been achieved in terms of the science-business link, where the university works to respond to the needs of the territory, strengthening the dialogues on both sides. The work was carried out at an Ice Cream Plant, belonging to the province of Holguín, Cuba. In it, daily production levels have been reduced in the last quarter of 2020, presenting greater difficulties in the production area. For the development of the same, the sampling of instantaneous observations, timing, individual photography, the interview and the MedTrab software were used as techniques and tools. In addition, as a methodology, the general method of problem solving. As a result of the diagnosis, it was obtained that in the production area the use of the working day is 83.75%, being unfavorable for the production process, where the packaging process has a greater influence, presenting the main difficulties. In this process it was found that the performance standard had not been defined and multiple losses of time were manifested. For these reasons, based on the study, the performance standard for the packing worker was determined, being 3,245 pots of 450 ml per day, solutions were proposed and actions aimed at improving the current situation in the area under study were projected.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".