Los Alamos County Library System Library Conversations Series will present author Ginger Gaffney reading from her book Half Broke, Thursday March 4 at 7 p.m.
‘Half Broke’ is a gorgeous, life-affirming memoir by a top-ranked horse trainer that offers profound insight into the fascinating ways both horses and humans seek relationships to survive. To attend the session, register HERE.
At the start of this remarkable story of recovery, healing, and redemption, Velarde-based author Ginger Gaffney answers a call to help re-train troubled horses at the Delancey Street Ranch in San Juan Pueblo.. The horses are scavenging through the dumpsters, and kicking and running down the residents when they bring the trash out after meals. One horse is severely injured.
The horses and residents arrive at the ranch broken in one way or many: the horses are defensive and terrified, while the residents, some battling drug and alcohol addictions, are emotionally and physically shattered. With deep insight into how animals and humans communicate through posture, body language, and honesty of spirit, Gaffney walks us through her struggle to train the untrainable.
Gaffney peels away the layers of her own story―a solitary childhood, painful introversion, and a transformative connection with her first horse, a filly named Belle―and narrates how she, too, learns to trust people as much as she trusts horses. Over her year-long odyssey, the group experiences triumphs and failures, brave recoveries and relapses, as well as betrayals and moving stories of trust and belonging.
Resonant, smart, and beautifully written, Half Broke tears at the heart of what it takes to find wholeness after years of trauma and offers profound insight on how working with animals can satisfy our universal need for connection.
Next up in the series will be the March 18 Screening of Shalini Kantayya’s film Coded Bias in partnership with NM PBS and the Society for Professional Journalists. Coded Bias features the work of MIT Media Lab researcher Joy Buolamwini, who discovers that many facial recognition technologies fail more often on darker-skinned faces or the faces of women than others, and delves into an investigation of widespread bias in the technology that shapes our lives.