Where Are Ontario’s Respiratory Therapists Working?
Bibliographic record
Abstract
Registered respiratory therapists (RRTs) aid in the diagnosis and treatment of respiratory illness and cardiopulmonary disorders, conditions that are increasingly being managed in settings other than the hospital sector.However, analysis of a longitudinal data set of Ontario' s RRTs (2,903) from 1996 to 2007 demonstrates that the majority of RRTs work full-time in the hospital sector, where retention is high.despite a policy direction encouraging the shift of the site of care from the hospital sector to the community/home, this has had little impact on where RRTs work, raising the question of who is providing respiratory services in the community. RésuméLes thérapeutes respiratoires autorisés (TRA) apportent leur aide dans le diagnostic et le traitement des maladies respiratoires et cardiopulmonaires, des états de santé qui sont de plus en plus traités dans des établissements autres que le secteur hospitalier.Cependant, l' analyse d'un ensemble de données longitudinales sur les TRA de l'Ontario (2903 personnes) de 1996 à 2007 démontre que la majorité des TRA travaillent à temps plein dans le secteur hospitalier, où le taux de conservation du personnel est élevé.malgré une directive politique visant à favoriser le transfert du point de service du secteur hospitalier vers le secteur communautaire ou domiciliaire, il y a eu peu de changement dans le lieu de travail des TRA, ce qui soulève la question à savoir qui offre des services respiratoires en milieu communautaire.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".