Economic hardships during COVID-19 and maternal mental health: Combining samples with low incomes across three cities.

The COVID-19 pandemic increased maternal depression and anxiety, imperiling both mothers' own wellbeing and that of their children. To date, however, little is known about the extent to which these increases are attributable to economic hardships commonly experienced during the pandemic: income loss, job loss, and loss of health insurance. Few studies have examined the individual impacts of these hardships, and none have lasted beyond the first year of the pandemic.

Reactive Inhibitory Control Precedes Overt Stuttering Events.

Research points to neurofunctional differences underlying fluent speech between stutterers and non-stutterers. Considerably less work has focused on processes that underlie stuttered vs. fluent speech.

Linguistic features of stuttering during spontaneous speech.

Purpose: Previous work shows that linguistic features (e.g., word length, word frequency) impact the predictability of stuttering events.

A large-scale analysis of racial disparities in police stops across the United States.

We assessed racial disparities in policing in the United States by compiling and analysing a dataset detailing nearly 100 million traffic stops conducted across the country. We found that black drivers were less likely to be stopped after sunset, when a 'veil of darkness' masks one's race, suggesting bias in stop decisions. Furthermore, by examining the rate at which stopped drivers were searched and the likelihood that searches turned up contraband, we found evidence that the bar for searching black and Hispanic drivers was lower than that for searching white drivers.

Predictive Analytics for City Agencies: Lessons from Children's Services.

Many municipal agencies maintain detailed and comprehensive electronic records of their interactions with citizens. These data, in combination with machine learning and statistical techniques, offer the promise of better decision making, and more efficient and equitable service delivery. However, a data scientist employed by an agency to implement these techniques faces numerous and varied choices that cumulatively can have significant real-world consequences.