La atenuante analógica de cuasiprescripción. Especial referencia a los delitos de corrupción
Bibliographic record
Abstract
El presente trabajo se ocupa del estudio de la denominada atenuante analógica de cuasiprescripción, la cual ha sido creada en el ámbito de la jurisprudencia española, abordando la evolución que ha experimentado la misma tanto en lo referente a los requisitos exigidos, como a su ámbito de aplicación, o modalidades. Así mismo, se analizan las dos vías de establecimiento de “la análoga significación” –prescripción y dilaciones indebidas-, concluyendo el artículo con una crítica sistemática de la figura de la cuasiprescripción en relación a: sus diferentes fundamentaciones, los elementos del delito, los fines de la pena, las causas de extinción de la responsabilidad penal, el proceso penal o la política criminal.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".