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Patterns of privilege: A total cohort analysis of admission and academic outcomes for Māori, Pacific and non-Māori non-Pacific health professional students

Overview of attention for article published in BMC Medical Education, October 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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1 policy source
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1 X user

Citations

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14 Dimensions

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89 Mendeley
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Title
Patterns of privilege: A total cohort analysis of admission and academic outcomes for Māori, Pacific and non-Māori non-Pacific health professional students
Published in
BMC Medical Education, October 2016
DOI 10.1186/s12909-016-0782-2
Pubmed ID
Authors

Erena Wikaire, Elana Curtis, Donna Cormack, Yannan Jiang, Louise McMillan, Rob Loto, Papaarangi Reid

Abstract

Tertiary institutions are struggling to ensure equitable academic outcomes for indigenous and ethnic minority students in health professional study. This demonstrates disadvantaging of ethnic minority student groups (whereby Indigenous and ethnic minority students consistently achieve academic outcomes at a lower level when compared to non-ethnic minority students) whilst privileging non-ethnic minority students and has important implications for health workforce and health equity priorities. Understanding the reasons for academic inequities is important to improve institutional performance. This study explores factors that impact on academic success for health professional students by ethnic group. Kaupapa Māori methodology was used to analyse data for 2686 health professional students at the University of Auckland in 2002-2012. Data were summarised for admission variables: school decile, Rank Score, subject credits, Auckland school, type of admission, and bridging programme; and academic outcomes: first-year grade point average (GPA), first-year passed all courses, year 2 - 4 programme GPA, graduated, graduated in the minimum time, and composite completion for Māori, Pacific, and non-Māori non-Pacific (nMnP) students. Statistical tests were used to identify significant differences between the three ethnic groupings. Māori and Pacific students were more likely to attend low decile schools (27 % Māori, 33 % Pacific vs. 5 % nMnP, p < 0.01); complete bridging foundation programmes (43 % Māori, 50 % Pacific vs. 5 % nMnP, p < 0.01), and received lower secondary school results (Rank Score 197 Māori, 178 Pacific vs. 231 nMnP, p < 0.01) when compared with nMnP students. Patterns of privilege were seen across all academic outcomes, whereby nMnP students achieved higher first year GPA (3.6 Māori, 2.8 Pacific vs. 4.7 nMnP, p < 0.01); were more likely to pass all first year courses (61 % Māori, 41 % Pacific vs. 78 % nMnP, p < 0.01); to graduate from intended programme (66 % Māori, 69 % Pacific vs. 78 % nMnP, p < 0.01); and to achieve optimal completion (9 % Māori, 2 % Pacific vs. 20 % nMnP, p < 0.01) when compared to Māori and Pacific students. To meet health workforce and health equity goals, tertiary institution staff should understand the realities and challenges faced by Māori and Pacific students and ensure programme delivery meets the unique needs of these students. Ethnic disparities in academic outcomes show patterns of privilege and should be alarming to tertiary institutions. If institutions are serious about achieving equitable outcomes for Māori and Pacific students, major institutional changes are necessary that ensure the unique needs of Māori and Pacific students are met.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
New Zealand 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 15%
Student > Postgraduate 8 9%
Student > Master 8 9%
Student > Ph. D. Student 7 8%
Student > Bachelor 6 7%
Other 18 20%
Unknown 29 33%
Readers by discipline Count As %
Medicine and Dentistry 16 18%
Nursing and Health Professions 15 17%
Social Sciences 9 10%
Psychology 5 6%
Arts and Humanities 4 4%
Other 10 11%
Unknown 30 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 December 2019.
All research outputs
#6,984,197
of 22,896,955 outputs
Outputs from BMC Medical Education
#1,218
of 3,338 outputs
Outputs of similar age
#106,167
of 320,352 outputs
Outputs of similar age from BMC Medical Education
#22
of 64 outputs
Altmetric has tracked 22,896,955 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 3,338 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 62% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 320,352 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.