Determinantes del acceso al sistema de seguridad social en pensiones en Colombia durante el año 2016
Bibliographic record
Abstract
El presente artículo tiene como objetivo estudiar los determinantes del acceso en el Sistema de Seguridad Social en Colombia a partir de los microdatos de la Gran Encuesta Integrada de Hogares –GEIH del DANE para el año 2016. Por medio de un modelo probit bivariado, se mide el efecto de características tales como el nivel educativo, el género, la categoría ocupacional y la ubicación geográfica en la probabilidad de cotizar al sistema de seguridad social en pensiones y salud. Como hallazgo principal, se destaca que la población con menor escolaridad, los trabajadores por cuenta propia y residentes de zonas rurales reportan la probabilidad de cotizar al sistema de seguridad social en pensiones más baja de todos los trabajadores.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.017 |
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; both teacher heads agree on what is shown here.
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".