Mortality due to non-existence of child restraint system in India
Bibliographic record
Abstract
Road crashes are the leading cause of unnatural death among children all over the world. India tops the global list of fatalities from road crashes and the rate is increasing every year. Children accounted for 6.1% of the total accidental deaths due to motor vehicle crashes in 2013 in India. Despite such high rates of child fatalities in motor vehicle crashes, there is currently no law in India regarding the use of child restraint systems, despite various studies demonstrating that failure to use child restraints is associated with increased fatal injury. According to the World Health Organisation, if correctly installed and used, child restraints reduce deaths among infants by approximately 70% and deaths among small children by 54–80%. It has been made compulsory by law to use child restraint systems in many developed countries such as USA, England, Australia and Canada, but developing countries like India, lack such laws. We report a motor vehicle crash wherein a two-month-old male baby was travelling unrestrained on his mother’s lap in the rear of a car driven by the child’s uncle who was wearing a seatbelt. The crash proved fatal for the baby, who suffered a severe head injury, while the other two occupants of car, both adults, escaped the crash with minor injuries. Child fatality may have been avoided by the use of proper child restraint systems. Strict implementation of existing laws, formulation of new laws regarding child safety and public awareness are necessary to reduce child fatalities in road crashes. Along with this case report are discussed the existing laws of child restraint systems all over the world and the need for implementation of such laws in developing countries like India.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".