A methodological proposal to evaluate the cost of duration moral hazard in workplace accident insurance
Bibliographic record
Abstract
The cost of duration moral hazard in workplace accident insurance has been amply explored by North-American scholars in both the USA and Canada. Given the current context of financial constraints in public accounts and particularly in the Social Security system, we feel that the issue merits inquiry in the case of Spain. The present research also posits a methodological proposal using the econometric technique of stochastic frontiers, which allows us to break down the duration of work-related leave into what we term “economic days” and “medical days”. Our calculations indicate that during the seven-year period spanning 2005 to 2011, the cost of sick leave amongst full-time salaried workers amounted to 5,830 million Euros (in constant 2011 Euros). Of this total, and bearing in mind that “economic days” are those attributable to duration moral hazard, over 2,500 million Euros might be linked to workplace absenteeism. It is on this figure where economic policy measures might prove more effective.
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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 | 0.039 | 0.122 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".