Project management using the PMBOK to improve productivity in the pastry industry in Huancayo
Bibliographic record
Abstract
Productivity in companies is a vital element for survival in a competitive and often unequal market, therefore the implementation of the PMBOK in the pastry industry is necessary to provide a standardized framework that allows clearly define objectives, activities, and responsibilities, improving communication and control of scope, time and costs; The research aimed to establish the impact of project management applying the PMBOK in improving productivity in the pastry industry in Huancayo. Basic research developed under a quantitative and correlational level approach, data was collected from 10 companies in the bakery and pastry industry in the city of Huancayo located in the Department of Junín. The information was processed and modeled through structural equations based on PLS. The results indicate a Spearman Rho correlation coefficient of 0.799 with a significance level of 0.000, demonstrating a strong positive relationship between the variables analyzed. Likewise, the general hypothesis is confirmed, which establishes a significant relationship between project management and continuous improvement through the implementation of the PMBOK approach.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".