Notice bibliographique
Résumé
These approaches complement one another while adding to our overall understanding of rural nursing practice. For example, the RNDB had not previously been analysed with rural nurses in mind. The demographic profile of rural RNs was generated for the first time for Canada as a whole and for the individual provinces and territories.(18) The documentary analysis takes a critical view of the policy context within which rural nurses practise.(19) The national survey has collected an abundance of information about rural nurses' work, quality of work life and degree of work satisfaction. And the experiences that nurses relate in the narrative approach bring to life the challenges and rewards of working in a variety of rural settings. A national survey of RNs working in rural and remote areas has been completed using a mailed questionnaire and followup based on Dillman's tailored design method.(29) The 3,933 eligible respondents represent all provinces and territories and an overall response rate of 68 per cent after correcting for duplicate registrations, address problems, and ineligibility (e.g., living rural, working urban). Sampling was done in collaboration with the professional nursing associations of each province and territory, using the databases of all RNs with active registration, while maintaining anonymity and confidentiality. The sampling strategy was twofold. First, a stratified random sample was selected from RNs with rural addresses(30) in each of the 10 provinces. Second, the questionnaire was mailed to the total population of Canadian RNs who indicated on their registration forms that their primary workplace was a nursing station or outpost setting and to all RNs registered in the territories (as an attempt to capture "remote" areas). Based on a total population of 229,813 RNs in Canada,(31) with stratification by province and assuming that the ratio of rural/urban nurses was similar to the rural/urban population proportions in the provinces,(32) we determined that 3,500 rural nurses would provide estimates that are statistically significant (p <.05) nationally, with a 90 per cent confidence level provincially. Rural nurses have many reasons to celebrate: they provide care to individuals and families of all ages, for a variety of conditions, in a range of rural and remote settings. Although they work in environments that are primarily governed by urban-centric policies and in workplaces where the quality of work life is often limited, the nurses reveal their passion and dedication to their communities and to practising in rural and remote areas through their stories and their survey comments. The nature of rural and remote nursing is deceiving; its complexity is seen during the nurses' interactions, first as community members and then as professionals. Rural nurses are often charting new courses in their communities and workplaces. Muriel Strode said, "Do not follow where the path may lead. Go instead where there is no path and leave a trail."(33) Discovering the nature of nursing practice in rural and remote Canada through this national study is the first step on such a path, and hopefully the first of many \n \n \n \ntrails.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,018 |
| Communication savante | 0,017 | 0,008 |
| Science ouverte | 0,002 | 0,012 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,007 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».