Referentes legales para un marco protector de datos personales
Bibliographic record
Abstract
El presente ensayo tiene como objetivo fundamental establecer un marco referencial que permita analizar los antecedentes normativos de la protección de los datos personales en nuestro país, planteando como punto de partida los antecedentes en la Constitución General de la Republica y en la legislación secundaria tanto de carácter federal como local, regulando los bienes jurídicos del derecho a la intimidad y la privacidad. En un plano intermedio, se aborda la influencia de las tecnologías de la información y comunicaciones en el nuevo marco regulador a nivel federal con la aparición de un nuevo lenguaje y figuras jurídicas en la legislación civil, mercantil, procesal y de protección al consumidor. Finalmente, la aparición de la legislación federal y locales en materia de acceso a la información y transparencia gubernamentales, la ley de protección de datos personales del Estado de Colima, así como la reglamentación respectiva por parte de la LFTAIP, permiten afirmar que de manera incipiente se ha comenzado a fomentar un marco protector de los datos personales en nuestro país.
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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 | 0.016 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".