Joined January 2010
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There are numerous ways in which the Covid 19 response failed Māori. In this post I use Ministry of Health figures for Covid 19 deaths to explain why inequities for Māori are obscured in the publicly available data. link.medium.com/XOuTB30prtb
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It is a privilege to support this mahi: boosted.org.nz/projects/tino…

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Daniel Wilson retweeted
University of Auckland Staff to Vice-Chancellor Dawn Freshwater: "[R]everse your decision and to offer your full support to students and staff who may choose to exercise their right to protest by establishing a peaceful encampment on campus grounds" 🇵🇸 overland.org.au/2024/05/open…
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I see they've now opened up more non member tix. I had a hard time finding any overlap between the NZ Tech member companies and Māori Tech companies featured in the Toi Hangarau report toihangarau.nz/

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It would be very useful if more technical details of the Equity Adjustor Score were made public. If it uses models based on historical surgical wait time data found that longer wait times were positively correlated with factors like remote location and deprivation rating 1/4
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that shows that ethnicity as a factor _does_ correlate with longer time-to-surgery even though it ought not to. In the meantime, a lot of poor commentary is filling an information vacuum. 3/4
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Incidentally, here is a model trained on historical surgical data that does quantify a health equity gap: nzrisk.com/. Check the BJS article for details. 4/4

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The path to the surgical waitlist is not the same for everyone—there are inequities for Māori and Pasifika. An analogy would be a network of roads (the pathway to the surgical waitlist) that lead to a bridge (the surgical waitlist) where the surgery is represented by 1/n
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"These latter areas have got to be our focus, but the surgical wait list issues can be the leverage for the real action on these. Simply being successful in getting prioritised waiting lists happening is nowhere near enough on its own.” 10/n
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The use of this tool for election-year race-baiting has been disgusting. And unfortunately the public detail of how the score was developed is minimal. But there is potential to keep discussing these important matters and keep moving toward eliminating these inequities. 11/11
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Join the Centre of Machine Learning for Social Good (ML4SG) National Hui. The free event will be on Friday 23 June 2023 from 1-4pm. Visit the link to register eventbrite.co.nz/e/national-… Any Questions? Email: ogra439@aucklanduni.ac.nz #MachineLearning #NewZealand
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