Les notes « Observations de l’infirmière » du Département de psychiatrie de l’Hôpital Montfort : une source archivistique incontournable en santé mentale
Bibliographic record
Abstract
Introduction Nurses' notes are used primarily as a communication tool between nurses, doctors and member of the professional team to ensure continuity of patient care. They contain life-history of individuals with mental health disorders. This nurses' communication tool describes the patient care during hospitalization in acute psychiatric ward. In fact, these observations contained in the progress notes represent more than a simple picture of mental illness. They always tell a story constructed by socio-cultural norms.Objectives The purpose of this article is to demonstrate the value of these narratives data as a comprehensive source of information to understand the experience of mental health following the deinstitutionalization project.Results The use of nursing progress notes of the Psychiatric Department allows, among other things, a better understanding of the life course of some hospitalized patients. The narrative data in those documents enhance the intersection between personal experiences and social, institutional and professional structures. These primary sources offer a multitude of possibilities in mental health research and can be examined from different angles of analysis. They deserve to be exploited in future research project to increase our understanding of mental illness.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".