Integration of the social environment in a mobility ontology for people with motor disabilities
Bibliographic record
Abstract
BACKGROUND: Our contemporary understanding of disability is rooted in the idea that disability is the product of human-environment interaction processes. People may be functionally limited, but this becomes a disability only when they engage with their immediate social and physical environments. Any attempt to address issues of mobility in relation to people with disabilities should be grounded in an ontology that encompasses this understanding. PURPOSE: The objective of this study is to provide a methodology to integrate the social and physical environments in the development of a mobility ontology for people with motor disabilities (PWMD). METHODS: We propose to create subclasses of concepts based on a Nature-Development distinction rather than creating separate social and physical subclasses. This allows the relationships between social and physical elements to be modelled in a more compact and efficient way by specifying them locally within each entity, and better accommodates the complexities of the human-environment interaction as well. Based on this approach, an ontology for mobility of PWMD considering four main elements - the social and physical environmental factors, human factors, life habits related to mobility and possible goals of mobility - is presented. CONCLUSIONS: We demonstrate that employing the Nature-Development perspective facilitates the process of developing useful ontologies, especially for defining the relationships between the social and physical parts of the environment. This is a fundamental issue for modelling the interaction between humans and their social and physical environments for a broad range of applications, including the development of geospatial assistive technologies for navigation of PWMD. Implications for rehabilitation The proposed perspective may actually have much broader interests beyond the issue of disability - much of the interesting dynamics in city development arises from the interaction between human-developed components - the built environment and its associated entities - and natural or organic components. The proposed approach facilitates the process of developing useful ontologies, especially for defining the relationships between the social and physical parts of the environment. This is a fundamental issue for modeling the interaction between human -specially people with disabilities -and his social and physical environments in a broad range of domains and applications, such as Geographic Information Systems and the development of geospatial assistive technologies for navigation of people with disabilities, respectively.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| 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".