Organisation des services dans une urgence rurale éloignée : réflexions autour du cas de Fermont, Québec.
Bibliographic record
Abstract
INTRODUCTION: The goal of this study was to meet a small, remote emergency department's need to reflect on the minimum threshold of services to offer. The study's main objectives were to 1) provide a statistical profile of the emergency services in Fermont, Quebec, 2) assess the staff's and users' perception of the threshold of services offered and 3) propose solutions for improving care and services. METHODS: This case study was conducted with a participatory approach and a mixed methodology. We compared the results from a questionnaire on the emergency services that was validated during a previous study with the results concerning the other rural emergency services in Quebec as well as with national and provincial recommendations. The questionnaire concerned users' sociodemographic characteristics, the hospital's and the emergency services' descriptors, the services available locally, and the physician and nurse staff. Interviews were also carried out with 33 people (health care professionals, policy-makers and citizens). RESULTS: Fermont's emergency department is smaller than the average rural emergency department in Quebec. They have resources that are in some respects comparable to those of other emergency departments and in line with the recommendations; in other respects, their resources are rather limited. Respondents emphasized how important it is to take into account the environment's specific features when establishing the minimum threshold of services. The proposed solutions would promote collaboration, break down silos within professional practice and focus on training. CONCLUSION: Fermont's case aside, this exploratory case study highlights how important it is to adopt a pluralistic, participatory and local approach in order to support reflection on the minimum threshold of services in remote emergency departments and to improve their overall performance.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".