Analysis of informational and technological requirements for the respiratory therapy workshops in Peru
Bibliographic record
Abstract
This paper examines the informational and technological needs of the respiratory therapy (RT) workshops run by the Canadian respiratory therapists (RTs) and RT students at various healthcare centers in developing countries. Every year in the summer, a team of volunteers from Thompson Rivers University travels to various locations in Peru and China and offers 1-3 days theoretical lectures and practical workshops on the use of technology in the diagnosis, treatment, and care of patients with cardiopulmonary disorders. The primary goals of the workshops are to transfer theoretical and technological knowledge, to teach practical skills, and to exchange the practices of providing cost-effective health care to patients in major centers as well as in rural areas. Our study focuses on the requirements for informational and technological support in the delivery of the workshops in Peru. This field study addresses contextual factors which play a major role in the efficient and effective use of knowledge and technology for the educational advancement of local healthcare providers, and, consequently, for improvement in of the health status of the patients. This study is based on a qualitative approach to the problem and uses ethnographic in-field observations, interviews, and analysis of visual materials. The paper also describes the settings and overall educational context of the workshops, and examines communicational and technical challenges in volunteer-based medical education and training in diversified settings. The study investigates the use of low-cost and low-resource methods for the at-location and learner-centered medical education and training. Furthermore, the paper discusses the possible utilization of a computerized knowledge repository to support the educational processes and the communication process involving multiple languages.
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 | 0.006 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".