Les caractéristiques des tuteurs de résilience des étudiants en soins infirmiers vulnérabilisés
Bibliographic record
Abstract
Nursing training seems to make students vulnerable to stress or burnout. Nevertheless, the majority succeeded in this training. This positive recovery despite a deleterious context of study questions about this schooling, and on possible resilient mechanisms and tutors of resilience. This research paper in educational sciences will begin with a synthesis of the results of publications about stressors and risk's factors of burnout of these students. We will see how this schooling can be linked to the concept of vulnerability and resilience. Then, we will present the results and the thematic analysis of 30 semi-directive interviews. The objectives of those ones were: to check factors vulnerability of this training, to determine if resilient processes can be observed, and to identify the characteristics of the resilience tutors of these weakened students. After the presentation of the results and of the analysis, we will discuss the links between vulnerability, post-traumatic stress disorder and burnout. We will explain the concept of compassion as one of the predominant characteristics of tutors. Finally, concerning the relational posture of education's professionals, we will show how they could professionally support students' resilience.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".