Te Ara Whakamua: The Stasis of Māori Nursing over 4-Decades in Aotearoa: An Indigenous Case Study
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".