Social Support and Aging with a Spinal Cord Injury: Canadian and British Experiences
Bibliographic record
Abstract
The study set out to describe the support systems of a large multicenter sample of people with long-standing spinal cord injuries (SCIs) and to explore the effects of age, duration of injury, problems, demographics, and well-being on reporting of social support. It was part of a longitudinal study of aging and SCI, involving British and Canadian participants. A total of 290 participants were recruited from four large, well-established databases in the United Kingdom and Canada. The sample included individuals with an average age of 57 years and an average duration of 33 years. The study showed that informational support was perceived by participants as less available to them than either instrumental or emotional support. Further, it showed that age has a direct negative effect on satisfaction with social support but an indirect positive effect on availability of support, mediated by well-being. Disability, on the other hand, has an indirect negative effect on satisfaction, mediated by problems. According to the model developed and tested here, the availability of social support has a significant negative direct effect on the experience of problems, but the presence or absence of problems does not affect the availability of social support.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".