Incorporation of environmental factors into outcomes research
Bibliographic record
Abstract
In health and disability arenas, it is increasingly being recognized that removing or modifying environmental factors can have a greater influence over outcomes than many individually focused interventions. In 2001, the World Health Organization endorsed a major revision of its framework for assessing and classifying health, disability and handicap, conceptualizing intervention and assessing outcome. This framework, the International Classification of Functioning, Disability and Health (ICF), is now defined by its recognition of the impact of environmental and personal factors on body function and structure, activities and participation in disablement. The ICF offers the potential to advance the understanding and integration of environmental dimensions into outcome research and measurement in health and disability. This paper proposes that a key future challenge for outcomes research is to understand and document environmental dimensions of health and disability using the precedent of the ICF. Potential steps and obstacles to this development are suggested, and the direct practice and broader policy applications gained by linking an international conceptual framework with clinical outcome research and practice 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 | 0.273 | 0.289 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".