Implementing the Global Plan of Action on workers' health: Components to protect health care workers
Bibliographic record
Abstract
Health care workers are at risk for percutaneous injuries and infection with blood born pathogens due to needle stick injuries with contaminated needles. The most common pathogens transmitted are hepatitis B, and C and HIV/AIDS. According to the WHO Global Plan of Action (GPA) a large gap exist between and within countries with regards to the health status of workers and their exposure to occupational risk. Less than 15% of the world's work forces have access to occupational health services despite the availability of effective interventions that can prevent occupational hazards, or protect and promote health in the workplace. The 2006 World Health Report declared that there is a global crisis in the health care work force. 1 in 400 of the world's health care workers work in Sub-Saharan Africa. 1 in 3 work in the U.S or Canada. The shortage of health care workers is worst in Southeast Asia and Sub-Saharan Africa. These countries have the highest burden of exposure to contaminated sharps. They rarely, if ever monitor the exposure or health impact of occupational ailments and injuries on workers. Many injuries are unreported. Occupational health services in the developing world are virtually non existent. Many health care workers leave their home countries and go to work in other countries where the working conditions, occupational services included, are better. The inability of countries to provide the necessary numbers of health care workers to provide a high level of health coverage is a threat to national and international public health security. Immunizing health care workers against hepatitis B and providing them PEP, PPE, education and safety training is an essential part of increasing and maintaining the numbers of health care workers in the critical shortage areas.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".