Consideraciones y estrategias para la implementación de un sistema de gestión de la calidad ISO 9001 en el marco del Licenciamiento y la Acreditación de la Educación Superior Universitaria en el Perú
Bibliographic record
Abstract
The new University Law has marked a before and\nafter in the peruvian educational context with\nprospective towards a more competitive market.\nThe quality management plan of the Licensing\nand the quality management system (QMS) of the\naccreditation facilitate the functional change of the\nuniversity towards systemic management based on\nprocesses. However, before the implementation of\nthe QMS is necessary some considerations such us\nWhat is quality and what for?, What is the purpose\nof education in our environment?, What is education\nwith quality or educational quality?, What is a quality\nmanagement plan?, What is quality management?,\n¿What is a quality management system? What\nis quality assurance? The university has its own\nregulations, its own policy of quality assurance\nand its own behaviors that makes it different from\nother organizations; therefore, in this new context,\nwe propose some considerations and strategies for\nimplementation, according to the ISO 9001 standard\nof a QMS in universities and their study programs.\nThis implementation should not be for fashion,\nobligation, status, or marketing; it must be to show\nwith evidence that the activities of the educational\norganization are done in a consistent manner and\nwith continuous improvement to achieve excellence\nin the management of the professionalization of\nhuman talent for employability, the generation of\nknowledge with quality and the development of the\ninnovation in our country.
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How this classification was reachedexpand
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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 teacher head, 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".