When her phone rang in February, Mashawn Cross was skeptical of the gentle voice offering help at the end of the line.
“You said you do what? And you’re with who?” the 52-year-old recalled saying.
Cross, who wasn’t working because of her ailing back and knees, was scraping by on roughly $200 a month in aid plus whatever she could make from recycling bottles and cans. Her gas and electric bills were chewing up her checks. She had been in and out of the emergency room, her doctor said she might have to get a colostomy bag, and depression was bedeviling her day by day.
Kourtni Gouché listened and began to help. The L.A. County caseworker helped get household supplies for Cross so she could save money and cover her utility bills. She offered to get her a new bed to soothe her pained back. She began connecting Cross to programs to ease her depression and get her off cigarettes, something Cross has long wanted but struggled to do.
“I feel like I’ve got a friend right here,” Cross said, occasionally growing teary as she exalted the caseworker who had kept coming through for her. In her apartment in a South L.A. duplex, over the whir of a box fan, she abruptly remembered a question she had forgotten to ask Gouché during their regular talks.
“How did you get my name to start with?” Cross asked.
The answer is an unusual mobilization of data analysis to try to head off homelessness before it starts.
Cross is part of a rare effort by L.A. County to marry predictive modeling — a tool used to forecast events by tracking patterns in current and historical data — with the deeply personal work of homelessness prevention.