The Human Activity Assistive Technology Model
Bibliographic record
Abstract
The Human Activity Assistive Technology (HAAT) model was first developed by Cook and Hussey to guide the selection of the most appropriate assistive technology (AT) to assist an individual with activity completion. The model developers have continued its evolution with updates made in 2002 and 2008. Each version of the model includes the same four components: the human, activity, and AT interacting within a context. The most recent iteration of the model portrays the visual as a three-dimensional sphere with equal portions designated for the human, activity, and AT embedded within a cube to represent the context. In 2008, Cook and Polgar described the relationship between the HAAT model and other frameworks/models familiar to occupational therapists (OTs) including the International Classification of Functioning, Disability and Health (ICF), the Person-Environment-Occupational Performance (PEOP) Model, and the Canadian Model of Occupational Performance and Enablement (CMOP-E). These frameworks and models can be used to define the components of the HAAT model further and are similar in terms of their interactive nature and holistic views of people, their environments, and the factors that help them participate in activities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".