Te Ara Whakamua: The Stasis of Māori Nursing over 4-Decades in Aotearoa: An Indigenous Case Study
Notice bibliographique
Résumé
This thesis investigates the static state of the Māori nursing workforce in New Zealand over the past 40 years; exploring the barriers to recruitment, retention, and progression within the profession. Despite Māori comprising 19% of the New Zealand population, their representation in the nursing workforce remains disproportionately low at approximately 7%. This disparity persists despite numerous policies, strategies, and calls to address inequities in the health system. A robust Māori nursing workforce is critical for achieving health equity, as it ensures culturally concordant care and addresses the systemic and institutional barriers that contribute to health disparities for Māori. Using a qualitative case study approach, guided by Kaupapa Māori principles, this research set out to explain how systemic, cultural, and historical factors impacted the Māori nursing workforce. Three embedded units of analysis—Māori student and registered nurses, key stakeholders, and a review of grey literature—provided the foundation for this inquiry. These data sources were systematically analysed to identify recurring themes and eventually develop key interpretations. The findings revealed entrenched issues of systemic racism, economic hardship, ineffective leadership, and political indifference that have collectively hindered the growth of the Māori nursing workforce. Three interpretations emerged from the synthesis of data: False Hope and Empty Promises, highlights the failure to implement long-standing recommendations to support Māori nurses; Smoke and Mirrors, examines the superficial measures that create an illusion of progress while failing to address root causes; and Complicit Disregard, identifies systemic neglect and inaction that perpetuates disparities within the profession. These interpretations demonstrate the persistent barriers to equity in nursing and highlight the urgency of systemic change. This thesis proposes the Taurakohia Model, a comprehensive framework designed to address these challenges and promote meaningful change. Drawing on decades of research and the voices of participants, the model offers actionable recommendations to support recruitment, retention, and professional development for Māori nurses. It emphasises the need for culturally responsive education, robust support systems for Māori students, and the establishment of more Māori-led nursing programmes to create pathways aligned with Māori aspirations. The findings of this research have significant implications for nursing education, leadership, and policy in New Zealand. Addressing the disparities within the Māori nursing workforce requires an unwavering commitment to honouring Te Tiriti o Waitangi and dismantling systemic racism within healthcare institutions. By implementing the recommendations from this research, it is possible to create a more equitable and inclusive nursing workforce that meets the needs of Māori and contributes to a more just and effective health system for all New Zealanders. This thesis concludes by highlighting the need for further research into political advocacy, nursing governance, and a review of cultural safety as an effective framework for implementing transformative praxis. It calls for longitudinal studies to evaluate the implementation of Bachelor of Nursing Māori programmes and their impact on workforce development. By addressing these gaps, the findings of this research offer a pathway to sustainable change for the Māori nursing workforce.
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 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 | 0,001 | 0,000 |
| 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 | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».