SNA Measurement of Real Income: An Application to North American Economies
Bibliographic record
Abstract
El reporte Stiglitz-Sen sobre la medicion del progreso economico proporciona un impulso para examinar el tipo de informacion que las agencias estadisticas presentan, asi como un enfoque de medicion economica. Por lo tanto, este articulo sigue las recomendaciones contenidas en el Sistema de Cuentas Nacionales (SCN) 1993 para el calculo del ingreso real agregado en vez del PIB real, para demostrar la utilidad de los datos de cuentas nacionales actualmente producidos. El documento incluye ajustes para los precios relativos referidos, como ganancia del comercio (el efecto combinado cambia los terminos del comercio y la proporcion de los precios de bienes comercializados y no comercializados), y para las entradas a la cuenta corriente diferentes de la balanza comercial. Estos ajustes pueden hacerse usando la informacion de cuentas nacionales ampliamente disponible a un costo minimo para las agencias estadisticas. El articulo sigue las recomendaciones del SCN 1993 y calcula el ingreso real para Mexico, Estados Unidos de America y Canada. El resultado ilustra hasta donde los factores de la produccion influyen en el progreso de una nacion, comparado con otras naciones o basado en la habilidad del pais para comprar los bienes y servicios que sus ciudadanos desean
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".