Bibliographic record
Abstract
Previous research exploring the relationship between litigation status and the symptoms of the plaintiff has been inconsistent and limited by methodological difficulties. This longitudinal study addressed many of the methodological shortcomings of previous research and examined the relationship between litigation status, employment, depression, pain and disability over the duration of the compensation process. Two hundred chronic back pain participants were selected from patients who attended an initial assessment interview at a pain centre. According to their litigation and employment status these patients were divided into four groups, namely a non-litigating non-working group, a non-litigating working group, a litigating non-working group and a litigating working group. All participants completed three questionnaires, one at intake, one at a minimum of 2 years later (for litigants during the litigation process), with the final questionnaire completed at a minimum of 15 months thereafter (for litigants after they had settled their claim). Questionnaires contained measures of pain (Visual Analogue Scale, Short Form McGill Pain Questionnaire), depression (Zung Self-Rating Depression Scale), and disability (Oswestry Disability Questionnaire). Overall participants who were working scored lower on all the measures than did participants who were not working. On the other hand participants who were litigating scored higher on all the measures than did participants who were not litigating. There was a significant time effect on all measures but this was qualified on some measures by the interactions of time with litigation status and work status. The present research further demonstrated that both litigation and employment were significant factors influencing recovery from injury.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".