Disability in sustainability theories, models, and frameworks: a scoping review guided by the international classification of functioning and the sustainable development goals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This review builds upon existing policy and research synergies between the World Health Organization’s (WHO) International Classification of Functioning (ICF), the Sustainable Development Goals (SDGs), and the Social Determinants of Health (SDH) Framework to identify contributions of a disability perspective to sustainability. Focusing on synthesized information from academic theories, models, and frameworks (TMFs) in peer-reviewed research, journal articles published in English and indexed in the Web of Science, Scopus, and PubMed were screened for relevance. Data charting resulted in three categories of TMF-style evidence: 1) Sustainability TMFs, 2) Interdisciplinary TMFs, and 3) Disability TMFs and other informing perspectives. A narrative summary of sustainability TMFs illustrated synergistic convergence with the Convention on the Rights of Persons with Disabilities (CRPD); as such, solutions that support the CRPD may have the potential to co-support sustainable development and vice versa. Two other categories of evidence led to a lens of TMF complexity as well as multiple connections between environmental (ecological) sustainability and disability. As guided by the SDGs, the outline of evidence resulted in two frameworks. First, a framework facilitates the mapping of key synergies such as transportation and built environment to minimize travel distance and reduce land use, climate emissions, air pollution, and travel cost, time, and risk – which in turn influence access to food, school, employment, healthcare, and community participation under the SDGs. Second, a framework is collated to consider ten guiding principles, under which the complexity of sustainability-disability TMFs can be streamlined to inform future policy and practice.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.152 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it