Effect of Eliminating Compensation for Pain and Suffering on the Outcome of Insurance Claims for Whiplash Injury
Bibliographic record
Abstract
BACKGROUND AND METHODS: The incidence and prognosis of whiplash injury from motor vehicle collisions may be related to eligibility for compensation for pain and suffering. On January 1, 1995, the tort-compensation system for traffic injuries, which included payments for pain and suffering, in Saskatchewan, Canada, was changed to a no-fault system, which did not include such payments. To determine whether this change was associated with a decrease in claims and improved recovery after whiplash injury, we studied a population-based cohort of persons who filed insurance claims for traffic injuries between July 1, 1994, and December 31, 1995. RESULTS: Of 9006 potentially eligible claimants, 7462 (83 percent) met our criteria for whiplash injury. The six-month cumulative incidence of claims was 417 per 100,000 persons in the last six months of the tort system, as compared with 302 and 296 per 100,000, respectively, in the first and second six-month periods of the no-fault system. The incidence of claims was higher for women than for men in each period; the incidence decreased by 43 percent for men and by 15 percent for women between the tort period and the two no-fault periods combined. The median time from the date of injury to the closure of a claim decreased from 433 days (95 percent confidence interval, 409 to 457) to 194 days (95 percent confidence interval, 182 to 206) and 203 days (95 percent confidence interval, 193 to 213), respectively. The intensity of neck pain, the level of physical functioning, and the presence or absence of depressive symptoms were strongly associated with the time to claim closure in both systems. CONCLUSIONS: The elimination of compensation for pain and suffering is associated with a decreased incidence and improved prognosis of whiplash injury.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".