Wage Adjustment Practices and the Link between Price and Wages: Survey Evidence from Colombian Firms
Bibliographic record
Abstract
Este artículo utiliza una encuesta a 1.305 firmas para evaluar las prácticas de ajustes salariales de las empresas en el mercado laboral colombiano. Específicamente, se analiza la frecuencia de los incrementos salariales y el vínculo entre los cambios de precios y salarios. Los resultados muestran que los salarios se ajustan anualmente, que los aumentos se concentran alrededor de la inflación observada y que ninguna empresa recortó los salarios. Además, los principales determinantes de dichos ajustes son factores asociados con el desempeño tanto de empresas como de trabajadores. La relación entre los cambios en salarios y precios es más fuerte en sectores donde los costos laborales representan una mayor proporción de los costos totales y en sectores con alta productividad laboral.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".