Development of employment indicators to advance the quality of spinal cord injury rehabilitation care: SCI-High Project
Bibliographic record
Abstract
CONTEXT: Employment and Return to Work (RTW) rates following spinal cord injury/disease (SCI/D) are low due to individual and impairments characteristics, secondary health conditions, social and environmental barriers, prior work experience, workplace supports and resources, and physical or psychosocial work demands. To improve RTW, the SCI-High Project team developed a set of Employment structure, process, and outcome indicators for adults with SCI/D in the first 18 months after rehabilitation admission. METHODS: A pan-Canadian Working Group of diverse stakeholders: (1) defined the Employment construct; (2) conducted a systematic search of available outcomes measures; (3) constructed a Driver diagram summarizing factors associated with employment. Subsequent facilitated meetings allowed for the creation of structure and process indicators, and the selection of outcome indicators. RESULTS: The structure indicator is the proportion of SCI/D rehabilitation programs with an employment resource center. The process indicator is the proportion of SCI/D rehabilitation inpatients who receive an employment assessment during inpatient rehabilitation. The intermediary and final outcome measures are the Readiness for Return-to-Work Scale (RRTW) and Work Productivity and Activity Impairment (WPAI). Scale A of the RRTW for those who are unemployed and Scale B of RRTW and WPAI will be used for those who are employed. CONCLUSION: This framework of Employment indicators intends to support the RTW needs of persons with SCI/D by ensuring that rehabilitation professionals provide opportunities to explore RTW within the first 18 months after rehab admission. Increased employment rates have the potential to enhance the wellbeing, health, and longevity of individuals with SCI/D.
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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 | 0.052 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| 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".