Join us Friday 1pm-4pm AEST Register: events.peanutproductions.com.au/wisa_impact_... I'll be a panelist with Australian Research Council Acting CEO Richard Johnson and Australia's Office for Women Executive Director Padma Raman PSM to discuss translating research into policy to advance EDI.
And the full write-up is available as a preprint on the OSF. The manuscript is currently under peer review. osf.io/jyq2f
If you'd like to read the research brief, you can download it here: womeninstem.org.au/wp-content/u...
This work was led by Dr Isabelle Kingsley with research assistance from Amanda Chan and Nicholas Ho. Professor Lisa Harvey-Smith and I round out the research team. We thank the participating organisations for their contributions to this research.
Future research examining cultural, racial, and other biases will be key to refining equity efforts in the STEM research sector.
Our research extends existing evidence on the efficacy of anonymisation of the peer review process in promoting equitable outcomes, including NASA's Dual-Anonymous Peer Review System: science.nasa.gov/researchers/...
Introduction NASA’s Science Mission Directorate is strongly committed to ensuring that the review of proposals is performed in an equitable and fair manner. To this end, SMD will evaluate proposals ...
By enhancing success rates for early career researchers, anonymisation may create a positive ripple effect in the career pipeline, diversifying the research pool, and supporting the broader issue - retaining and advancing researchers facing barriers in STEM research.
In sum, we found that anonymising applications for scientific equipment can enhance early-career researchers' chances of success. Since no prior gender gap existed in our data, anonymisation wouldn't be expected to impact gendered outcomes. Our results confirm this.
In relation to the analysed data, we use the term 'women' for gender data classified as female and 'men' for gender data classified as male. We acknowledge the limitations of the binarisation of a nonbinary construct.
Gender data provided by these entities included female, male, and indeterminate. Because applications for which the lead investigator gender was classified as indeterminate (n=4) were only present before anonymisation, we could not study the impact of anonymisation on this group.