Restraint System Usage in the Traffic Population. 1984 Annual Report
Bibliographic record
Abstract
This report presents findings from four independent studies on occupant restraint use for various segments of the traffic population. Field observations, collected in 19 U.S. cities from January through December, 1984, are the basis for this report. The four studies and their findings are as follows: (1) Driver Safety Belt Use: A total of 130,207 drivers stopped for traffic signals were observed during the 12 month period. 15.3 percent were observed to wear safety belts during the last data collection period (July to December). (2) Passenger Safety Belt and Child Safety Seat Use: Findings from this study are based on 108,076 passengers observed at shopping mall entrances and exists. Child safety seat usage (for infants and toddlers) increased throughout 1984, reaching a high in the third quarter (July to December) of 49.3 percent. The percent of toddlers, subteens, teens, and adults wearing safety belts during the third quarter was observed to be 8.1, 15.2, 7.2, and 13.4 percent, respectively. (3) Safety Seat Installation Characteristics: Observations were recorded on a total of 3,476 child safety seats in vehicles parked at shopping malls and 88.1 percent were observed in the toddler mode. For toddler seats that require securing by only the vehicle safety belt, 56.4 percent were used correctly. However, only 8.7 percent of toddler seats that require the safety belt and tether were used correctly. (4) Helmet Use by Operators and Passengers of Motorcycles and Mopeds: Driver and passenger helmet use was observed to be 66.6 and 54.0 percent, respectively, for 14,898 motorcycle observations. Moped observations totalled 1,085 and helmet use among drivers and passengers was observed to be 42.1 and 35.0 percent, respectively. /Abstract from report summary page/
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".