After multiple delays, the Pentagon finally authorized RAND to release its report with estimates of installation- and command-level risk of military sexual assault and harassment. This follow-on report draws from the same data collected in 2014, when I played a small role in the massive and groundbreaking RAND Military Workplace Study, which provided significant information about the nature, context, and prevalence of these scourges.
In this new research, RAND differentiates between “total risk,” largely driven by the demographic mix at the base (younger, junior ranking, unmarried service members are known to be at increased risk of experiencing harassment and/or assault), and “installation-specific risk,” which isolates the risk associated with an installation or command that is not explained by demographics. This portion of total risk may be linked to installation-specific features including command climate, local traditions, the surrounding community, or other factors that commanders could be able to tackle. RAND found very significant variations in installation-specific risk: in the Navy, for example, women’s risk could be up to twice as high on some ships.
What should be done now that RAND has demonstrated that it is possible to identify both total and installation-specific risk with this proof-of-concept research project?
Given the limitations of the data, I do not believe it should be used in isolation to deny promotions: this survey is a snapshot from four years ago that is not able to show whether rates of harassment or assault increased or decreased under a particular commander, who may not have led the unit for long enough before or throughout the time period covered to substantially affect the rates. Additionally, this research does not indicate what causes the differences in installation-level risk, which could include multiple factors outside the control of commanders.
But I do believe additional research, greater transparency, and targeted action are warranted. This preliminary research shows certain patterns – ships seem to be particularly high risk, for example – and an important next step is to identify what factors are likely to increase or decrease risk.
Read the full article at The Hill.