Potential Implications of Advanced Practice Radiography on the Canadian Healthcare System from Technologists Perspectives
Bibliographic record
Abstract
Advanced practice in healthcare has emerged as a meaningful way to optimize resources and improve the patient experience. Published studies from other countries have shown that the advancement of the radiographer’s role has been successful in a variety of healthcare systems. While the Canadian Association of Medical Radiation Technologists developed a framework for the advanced practice of technologists, formal training and certification for an advanced radiographer role has yet to be introduced within the Canadian healthcare system. Despite this, many technologists currently perform delegated tasks beyond the scope of their described role. Understanding more about these delegated tasks can shed light on potential implications of a formal advanced practice radiographer role in Canada. When interviewed, many technologists find that on-site training for performing these procedures is sufficient and they were able to observe improved patient care in the department. In conclusion, this paper is written to reiterate the evidence supporting the development of an Advanced Practice role for Radiological Technologists, as well as present the perspective of technologists who perform procedures outside of a conventional technologist role.
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.
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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".