Aplicaciones tecnológicas como factores de cambio en la regulación del servicio público de transporte individual de pasajeros con vehículos tipo rxi. Caso de estudio : Bogotá
Bibliographic record
Abstract
En el presente trabajo observará como desde el año 2011, con el ingreso del App Uber, la prestación del servicio público de transporte individual de pasajeros con vehículos tipo taxi ha sufrido grandes cambios, generando modificaciones en el esquema y el ingreso de nuevos actores quienes tienen la posibilidad de cobrar tarifas sin tener en cuenta lo contemplado en la regulación de estructura de costos y metodología tarifaria. Ejemplo de lo anterior es que, en uso de la plataforma tecnológica tanto vehículos especiales (blancos) como los particulares pueden prestar el servicio que en principio solo podrían hacer los taxis y cobrar una tarifa diferente a la señalada por la autoridad competente. A su vez, el regulador se enfrenta ante un gran desafío consistente en incorporar i
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".