Bibliographic record
Abstract
El desarrollo de la Educacion Fiscal no es un tema nuevo, sin embargo permanece el hecho de su importancia para la concientizacion de los ciudadanos hacia el pago de sus obligaciones con el Estado. Este trabajo tiene como objetivo describir el estado actual y real de la Educacion fiscal en Mexico respecto a otros paises, a traves de una serie de datos derivados de una relacion de caracteristicas de naciones de America Latina que fomentan la Educacion Fiscal descritas en Eurosocial del sector Fiscalidad, lidera das por el Instituto de Estudios Fiscales de Espana. Para este estudio se integran los paises norteamericanos: Canada y Estados Unidos; bajo este contexto se evalua la situacion nacional recurriendo a indicadores de porcentajes de recaudacion tributaria respecto del Producto Interno Bruto (PIB), asimismo el PIB per capita, mismos que permitan analizar y comparar los resultados entre los paises, asi como proponer conclusiones e identificar los desafios que coadyuven a la practica de la Educacion Fiscal en Mexico.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".