CÓMO SE RECAUDA EN AMÉRICA LATINA (*) Resultados de una encuesta sobre 17 Administraciones tributarias de América Latina 2006-2010
Bibliographic record
Abstract
Este documento es un resumen de un estudio de evaluación y prospectiva del estado de las Administraciones Tributarias (AA.TT.) en América Latina en el quinquenio 2006 –2010, basado en un una encuesta. Del análisis surge que la gran mayoría de las AA.TT. fueron dotadas de autonomía técnica y presupuestaria y se impulsó la profesionalización de su personal. Se produjeron importantes avances en la función de recaudación y el uso masivo de tecnologías para mejorar la información disponible. Sin embargo, los resultados muestran un considerable déficit en materia de fiscalización, cobranza coactiva y tributación internacional, en especial en Centroamérica, por lo que se hace necesaria una segunda generación de reformas que consolide los avances. El trabajo completo y la base de datos se encuentran en: http://www.ciat.org/index.php/en/products-and-services/ciatdata/tax-administration.html
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".