A framework for modelling the selection of assistive technology devices (ATDs)
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
PURPOSE: The previously published 'Framework for the conceptual modelling of assistive technology device (ATD) outcomes' assumes antecedent factors that inform it and influence its component variables. This paper proposes a model of factors influencing consumer predispositions and provider practices related to procuring a particular ATD, which is the starting point in the framework. METHODS: The relevant literature on a variety of factors that influence specific ATD selection is summarized. RESULTS: The decision that a particular ATD is an appropriate and desirable support for an individual is the result of a process which is affected by a broader societal climate that determines, in part, unique personal climates which then foster unique provider and consumer perspectives predisposing each to the selection of a particular ATD. CONCLUSIONS: The proposed 'Framework for modelling the selection of ATDs' can contribute to clinical practice and outcomes research by highlighting factors important to consider prior to ATD selection.
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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 | 0.004 | 0.007 |
| 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 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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