The role of Environment in the International Classification of Functioning, Disability and Health (ICF)
Bibliographic record
Abstract
PURPOSE: This paper provides a framework for understanding the impact of environmental factors on functioning when a person has a health condition. This understanding provides the rationale for including environmental factors in WHO's International Classification of Functioning, Disability and Health (ICF). METHOD AND RESULTS: This conceptual paper uses a review format to provide, firstly, an historical perspective on the integration of environmental factors into the understanding of disability and the ICF; secondly, a description of the overall ICF and, specifically, the environmental factors section; and thirdly, an overview of the interaction of a person with a health condition and the environment in which they live, and the outcome of disability. CONCLUSIONS: The ICF is a classification that allows a comprehensive and detailed description of a person's experience of disability, including the environmental barriers and facilitators that have an impact on a person's functioning. The recognition of the central role played by environmental factors has changed the locus of the problem and, hence, focus of intervention, from the individual to the environment in which the individual lives. Disability is no longer understood as a feature of the individual, but rather as the outcome of an interaction of the person with a health condition and the environmental factors.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".