TECHNOLOGY MANAGEMENT AS A CORE COMPONENT OF A CLIENT-CENTRIC PROSTHETIC ORTHOTIC PRACTICE MODEL
Bibliographic record
Abstract
Technological innovation has transformed how we communicate, work, and conduct business. Over the next decade how we experience health care both as health care professionals and as client-patients will also change significantly. This presents both an opportunity and a challenge to medical clinical professionals that are device-focused, including prosthetists orthotists, as they consider how best to adapt. Current prosthetic orthotic education and practice is heavily clinically weighted, with less emphasis being given to engineering and business skills. Yet all three are essential core elements of a successful, sustainable prosthetics orthotics practice. Furthermore, it is the latter two that will heavily influence the future face of prosthetics & orthotics. It is not certain how current prosthetic orthotic practitioners can best adapt in response. One solution, proposed in this editorial, could be by rebalancing their professional persona to equally weight the three essential core elements. The result, a Clinical Prosthetic Orthotic Technology Management Professional, would engage in a professional practice that is functionally grounded, uses a client-centric model and incorporate eight professional attributes: professional, advocate, scholar, leader, communicator, collaborator, assistive technology expert and business justification specialist. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/39001/29732 How To Cite: Raschke S.U. Technology management as a core component of a client-centric prosthetic orthotic practice model. Canadian Prosthetics & Orthotics Journal. 2022; Volume 5, Issue 2, No.1. https://doi.org/10.33137/cpoj.v5i2.39001 Corresponding Author: Silvia Ursula Raschke, PhDBritish Columbia Institute of Technology (BCIT), 3700 Willingdon Avenue, Burnaby, British Columbia, Canada.E-Mail: Silvia_Raschke@bcit.caORCID ID: https://orcid.org/0000-0001-7964-4295
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".