The Effects of Traffic Accidents on the Emergence of Psychological Disorders Among Drivers of “3rd. Category”: Private License in Jordan “A Field Research”
Bibliographic record
Abstract
The study aimed to know the effects of traffic accidents on the emergence of psychological disorders among drivers from “3rd category” private license in the city of Salt in Jordan. That would be through knowing whether the traffic accidents have an impact on the driver’s psychological trauma and if traffic accidents cause an emergence of state of depression, nervousness, and lack of concentration at work. A psychological trauma questionnaire which consisted of (17) paragraphs was used. In addition, a questionnaire which consisted of (28) paragraphs was laid out and spread over several pivots (depression, nervousness and the lack of concentration at work). The research sample has been formed of (50) drivers 14 of them were females, after that averages, and standard deviations and calculating of the value of the test (T) were extracted to come to the study conclusions. The study concluded that there were statistical differences which confirm that the drivers who were involved in traffic accidents have been exposed to psychological trauma, states of depression and nervousness. Also, the study indicated that there were no statistical differences between traffic accidents and the lack of concentration at work. Key words : Traffic Accidents; Psychological Disorders; Driving license from 3rd category; Depression; Nervousness; Emotion
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.027 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".