El narcotráfico en el Sur de España, más allá del Mal.
Bibliographic record
Abstract
RESUMEN Aproximación social desde diferentes perspectivas de la problemática del narcotráfico en el sur de España. Intentaremos dar respuestas a preguntas controvertidas y de actualidad, más allá del narcotráfico y el contrabando, ¿Que características y factores favorecen el narcotráfico en el sur de la Península Ibérica? ¿Cuáles son las cifras de delitos relacionados con la actividad del narcotráfico?, ¿Cuáles son las cifras de incautaciones de drogas ilegales predominantes en España y Europa? Veremos las consecuencias de las drogas y las adicciones. También veremos el glosario del narcotráfico, la utilización por parte de las organizaciones del narcotráfico de las personas migrantes que quieren cruzar el Estrecho de Gibraltar, como medio para asegurar los alijos, así como el mito del contrabandista, y la desinformación. ABSTRACT Social approach from different perspectives to the problem of drug trafficking in the South of Spain. We will try to give answers to controversial and topical questions, beyond drug trafficking and smuggling, characteristics and factors that benefit drug trafficking in the South of the Iberian Peninsula, the figures of crimes related to drug trafficking activity, as well as the figures of seizures of main illegal drugs predominant in Spain and Europe? We will look at the consequences of drugs and addictions. We will also look at the Glossary of drug trafficking. The use of migrants who want to cross the Strait of Gibraltar by drug trafficking organisations, as means shipments. Besides, we will analyze in more detail the Myth of the Smuggler, and misinformation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".