Hiding in plain sight: the absence of consideration of the gendered dimensions in ‘source’ country perspectives on health worker migration
Notice bibliographique
Résumé
BACKGROUND: Gender roles and relations affect both the drivers and experiences of health worker migration, yet policy responses rarely consider these gender dimensions. This lack of explicit attention from source country perspectives can lead to inadequate policy responses. METHODS: A Canadian-led research team partnered with co-investigators in the Philippines, South Africa, and India to examine the causes, consequences and policy responses to the international migration of health workers from these 'source' countries. Multiple-methods combined an initial documentary analysis, interviews and surveys with health workers and country-based stakeholders. We undertook an explicit gender-based analysis highlighting the gender-related influences and implications that emerged from the published literature and policy documents from the decade 2005 to 2015; in-depth interviews with 117 stakeholders; and surveys conducted with 3580 health workers. RESULTS: The documentary analysis of health worker emigration from South Africa, India and the Philippines reveal that gender can mediate access to and participation in health worker training, employment, and ultimately migration. Our analysis of survey data from nurses, physicians and other health workers in South Africa, India and the Philippines and interviews with policy stakeholders, however, reveals a curious absence of how gender might mediate health worker migration. Stereotypical views were evident amongst stakeholders; for example, in South Africa female health workers were described as "preferred" for "innate" personal characteristics and cultural reasons, and in India men are directed away from nursing roles particularly because they are considered only for women. The finding that inadequate remuneration was as a key migration driver amongst survey respondents in India and the Philippines, where nurses predominated in our sample, was not necessarily linked to underlying gender-based pay inequity. The documentary data suggest that migration may improve social status of female nurses, but it may also expose them to deskilling, as a result of the intersecting racism and sexism experienced in destination countries. Regardless of these underlying influences in migration decision-making, gender is rarely considered either as an important contextual influence or analytic category in the policy responses. CONCLUSION: An explicit gender-based analysis of health worker emigration, which may help to emphasize important equity considerations, could offer useful insights for the health and social policy responses adopted by source countries.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».