Una propuesta de empalmede las encuestas de hogaresbasada en la tasa dedesempleo
Bibliographic record
Abstract
El análisis acerca de los cambiosde metodología entre la EncuestaNacional de Hogares (ENH) y la EncuestaContinua de Hogares (ECH), permite ver una ruptura en el estudiode los indicadores del mercadolaboral que justifica el desarrollo deuna propuesta de empalme para lasvariables utilizadas en el cálculo delos indicadores del mercado laboral.Particularmente, este artículo trabajael empalme de la serie de la tasade desempleo nacional a siete ÁreasMetropolitanas desde marzo de 1985hasta diciembre de 2003, basándoseen el cálculo de un factor de correccióndefinitivo que es el producto dedos factores de corrección: uno pordefinición y otro por recolección, talcomo lo presentaron Suárez y Buriticá(2004). Los resultados del empalmemuestran que la serie corregidadisminuye aproximadamente 0.46puntos porcentuales, con respecto ala serie original. Asimismo, muestranque sólo es posible utilizar las ECHdel ano 2000 y el primer trimestre del2001 para empalmar las series.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".