Incidence of work and non‐work related disability claims in Brazil
Bibliographic record
Abstract
BACKGROUND: Sickness benefit claims are an important economic burden to society. This study aims to determine the incidence of sickness benefit claims in Brazil in 2008, exploring the role of economic activity. METHODS: Population-based study on sickness claims lasting longer than 15 days of sickness absence granted to private sector employees. Data on gender, age, economic activity, diagnosis, and work-relatedness were collected. RESULTS: The annual incidence of sickness benefits was 421.8/10,000 jobs, 435.4 for males and 452.0 for females. There were 3.5 times more non-work-related than work-related claims. The main diagnoses were injuries, musculoskeletal disorders, and mental disorders. Rates increased with age up to 59 years. Economic activity 37-Sewage had the highest incidence of non-work-related and work-related claims. CONCLUSION: The incidence of sickness benefits is higher among female and older workers. Economic activities show great variability of sickness benefit rates, work-relatedness, diagnostic categories, and gender.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".