"LIFE SATISFACTION AFTER TRAUMATIC SPINAL CORD INJURY: A COMPARISON OF LIFE SATISFACTION IN PEOPLE LIVING WITH PARAPLEGIA AND TETRAPLEGIA TO THE GENERAL CANADIAN POPULATION"
Bibliographic record
Abstract
Traumatic spinal cord injury (tSCI) can be a life changing event that has the potential to impact many aspects of life including subjective well-being.One component of subjective well-being that is commonly measured following tSCI is Life Satisfaction (LS).Despite this, it is difficult to find research that has made direct comparison between the levels of LS reported by tSCI survivors and the general population.To better understand the impact that tSCI has on LS, the present study compared the LS of individuals without a tSCI, to a large sample of individuals who are currently living with tSCI that resulted in either paraplegia or tetraplegia.Our analyses showed that individuals with tSCI report lower levels of LS, when compared to individuals without a tSCI, and that people with tetraplegia report lower LS than individuals living with paraplegia.We also determined whether people without a tSCI can make accurate predictions about how their LS would change is they sustained a tSCI resulting in paraplegia or tetraplegia.When participants without tSCI were asked to estimate their life satisfaction in both situations, they overestimated the impact of tSCI.The degree to which LS in tSCI survivors differs from individuals without a tSCI , reasons for the overestimations made by individuals without tSCI and implications of the findings are discussed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".