Tag Archives: journal club

Journal Club: Counter-measures for Implicit Bias

This long-read from vox.com would be 13 pages if I printed it, but it is for a general audience, so it’s not like a 13 page research paper.
http://www.vox.com/identities/2016/11/15/13595508/racism-trump-research-study

Linked from the link is this amazing video:

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Filed under diversity and inclusion

Journal Club: Reducing Bias in Academic Search Committees

Short article from the kick-off of a new IHME journal club, with a focus on diversity and health disparities: [link]

Topics that bubbled up in discussion: composition of search committees, pipeline issues and other barriers to attracting diverse candidates, the scale of the problem with systemic racism.

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Filed under education

Journal Club: Ten Frequently Asked Questions About Implicit Measures and Their Frequently Supposed, But Not Entirely Correct Answers

Second edition of the Diversity Lunch Discussion journal club, with a focus on the Implicit Association Test. Many participants also *took* an IAT—Rose suggests you try taking the Race IAT before our discussion tomorrow: https://implicit.harvard.edu/implicit/takeatest.html

So much knowledge and expertise in this group.

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Filed under education

CVRS analysis in Kiribati

To read: Mortality and life expectancy in Kiribati based on analysis of reported deaths

http://pophealthmetrics.biomedcentral.com/articles/10.1186/s12963-016-0072-6

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Filed under global health

Article I’m interested in: “Machine Learning and the Profession of Medicine”

Darcy AM, Louie AK, Roberts L. Machine Learning and the Profession of Medicine. JAMA. 2016;315(6):551-552. doi:10.1001/jama.2015.18421.

> Must a physician be human? …

http://jama.jamanetwork.com/article.aspx?articleID=2488315

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Filed under machine learning

To read in JAMA: Trends in Prescription Drug Use Among Adults in the United States From 1999-2012

Trends in Prescription Drug Use Among Adults in the United States From 1999-2012
http://jama.jamanetwork.com/article.aspx?articleID=2467552

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Filed under global health

Journal Club: Efficient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S.

Last week, we read Chien et al, Efficient mapping and geographic disparities in breast cancer mortality at the county-level by race and age in the U.S.  I’ve been very interested in these sort of “small-areas” spatial statistical methods recently, so it was good to see what is out there as the state of the art.  I think I’ve got something to contribute along these lines some day soon.

Maps in small multiples look just lovely, too:
usa

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Filed under statistics