El debate sobre la flexibilidad laboral en la India. Argumentos en contra de los acuerdos voluntarios
Bibliographic record
Abstract
Resumen Un punto candente del debate sobre flexibilización laboral en la India es la obligación de que las empresas de 100 asalariados o más obtengan permiso del Gobierno para los despidos. Quienes abogan por revocar dicha ley (o elevar sustancialmente el umbral de trabajadores) se basan en Basu, Fields y Debgupta (2009), cuya argumentación teórica a favor del despido y la contratación libres sobre la base de acuerdos voluntarios se cuestiona aquí: la recomendación política general de estos autores no se sostiene lógicamente ni siquiera en el marco de su propio modelo, por lo que esta alternativa de flexibilización sigue sin fundamento.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".