FOREIGN-TRAINED NURSES IN US HEALTHCARE DELIVERY
Notice bibliographique
Résumé
We at CGFNS International (the Commission on Graduates of Foreign Nursing Schools, Philadelphia, Pa) noted with interest the article by Polsky et al.1 We agree with their conclusions that foreign-trained nurses are a substantial part of the US nursing workforce and that the impact of foreign-trained nurses is likely to grow in coming years. Our own findings suggest that the trend in US employment of foreign-trained nurses has continued to grow in this decade, with increasing numbers of foreign-trained nurses applying to the CGFNS VisaScreen Program, a federal screening program for nurses seeking US occupational visas. The Philippines, India, Canada, and South Korea were the primary source countries for 2003–2006 Visa Screen applications.2 The important role of foreign-trained nurses in US health care delivery has been recognized for more than a decade3–5 and is clearly rooted in market forces. Polsky et al. raised concern that the “aggressive recruitment of nurses from overseas will not be met with equally vigorous assurance of the quality and skills of the immigrating nurses.”1(p895) As Polsky et al. indicated, foreign-trained nurses are more likely than their US counterparts to have a bachelor’s degree, comparable work experience, and higher income. What was not noted in the article is that the US government has established rigorous steps for assuring that foreign nurses entering the US workforce are qualified to do so. The 1996 immigration law6 requires that all foreign nurses undergo a screening program that verifies that their education is comparable to that of a nurse educated in the United States, their nursing licenses are valid and unencumbered, they have proficiency in written and spoken English, and they have passed a test of nursing knowledge, either the CGFNS Qualifying Examination or the US licensure examination. CGFNS was named in the 1996 immigration law to conduct the screening program, and through its VisaScreen Program, protects the US public by ensuring that the credentials and nursing knowledge of foreign nurses are comparable to those of nurses educated in the United States. Although it is true that the international migration of nurses has the potential of depleting the supply of vital professionals in some poorer nations that can ill afford to lose them, the issue is complex and must be examined within the context of the nurse’s right to migrate. The international migration of nurses provides individual and family opportunity for employment, income, and security that may not be available in the countries of origin. Moreover, the return of money home to the countries of origin is significant and can be used for investment, cutting poverty, and upgrading education.7
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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,001 |
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 ».