¿Existen Alternativas no Exploradas para el IVA en México? Lecciones de la OCDE
Bibliographic record
Abstract
El Impuesto al Valor Agregado es para Mexico una de las fuentes de ingreso mas importantes cuya recaudacion es relativamente facil de realizar. ?Que opciones mas alla de las vigentes podrian complementar su operacion en el contexto de una reforma fiscal, o acaso el sistema mexicano del IVA contempla las modalidades de gravacion idoneas o existen alternativas no exploradas? El presente articulo proporciona un bosquejo de aspectos generales del IVA en Australia, Nueva Zelanda, Canada, Francia y Reino Unido que ofrece una idea sobre la situacion del impuesto en esos paises y sobre cuestiones de caracter global que podrian complementar el caso del IVA en Mexico. Un acercamiento mas preciso a la situacion del IVA del pais o paises que despertaran interes, se generaria con el analisis de la normatividad que rige el correspondiente sistema de IVA. La informacion que reune el articulo proviene de un informe sobre la situacion del Impuesto al Valor Agregado en paises de la OCDE, realizado por la Direccion de Rendicion de Cuentas del Gobierno de Estados Unidos ante la perspectiva de llegar a establecer este impuesto en el gobierno federal de ese pais
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".