Join the Henry Ford Health - Healthcare Equity Book Club! A book related to culture or equity is selected each quarter. Discussions are both online and in person, and are moderated by our Henry Ford Health - Healthcare Equity Team.
You must be a Goodreads member to join the Book Club. Goodreads is a free site that hosts reading groups, lets you create lists of the books you've read and those you want to read. It's a great site to locate reading suggestions, too.
This will be a virtual book club meeting.
Please contact Amanda Kelly at akelly14@hfhs.org for the Webex Information. Amanda will forward the Webex connection information to you.
January 2024 Book Club Selections
Book Club selections may be checked out from the Sladen Library. Email us at sladen@hfhs.org or akelly14@hfhs.org or give us a call at 313-916-2550 and we can assist you with availability and delivery.
An NPR Best Book of the Year, exploring the impact of Latinos' new collective racial identity on the way Americans understand race, with a new afterword by the author Who are Latinos and where do they fit in America's racial order? In this "timely and important examination of Latinx identity" (Ms.), Laura E. Gómez, a leading critical race scholar, argues that it is only recently that Mexican Americans, Puerto Ricans, Cubans, Dominicans, Central Americans, and others are seeing themselves (and being seen by others) under the banner of a cohesive racial identity. And the catalyst for this emergent identity, she argues, has been the ferocity of anti-Latino racism. In what Booklist calls "an incisive study of history, complex interrogation of racial construction, and sophisticated legal argument," Gómez "packs a knockout punch" (Publishers Weekly), illuminating for readers the fascinating race-making, unmaking, and re-making processes that Latinos have undergone over time, indelibly changing the way race functions in this country. Building on the "insightful and well-researched" (Kirkus Reviews) material of the original, the paperback features a new afterword in which the author analyzes results of the 2020 Census, providing brilliant, timely insight about how Latinos have come to self-identify.
Caroline Criado Perez's Invisible Women: Data Bias in a World Designed for Men is a landmark, prize-winning, international bestselling examination of how a gender gap in data perpetuates bias and disadvantages women. #1 International Bestseller Winner of the 2019 Financial Times and McKinsey Business Book of the Year Award Winner of the 2019 Royal Society Science Book Prize Data is fundamental to the modern world. From economic development to health care to education and public policy, we rely on numbers to allocate resources and make crucial decisions. But because so much data fails to take into account gender, because it treats men as the default and women as atypical, bias and discrimination are baked into our systems. And women pay tremendous costs for this insidious bias: in time, in money, and often with their lives. Celebrated feminist advocate Caroline Criado Perez investigates this shocking root cause of gender inequality in Invisible Women. Examining the home, the workplace, the public square, the doctor's office, and more, Criado Perez unearths a dangerous pattern in data and its consequences on women's lives. Product designers use a "one-size-fits-all" approach to everything from pianos to cell phones to voice recognition software, when in fact this approach is designed to fit men. Cities prioritize men's needs when designing public transportation, roads, and even snow removal, neglecting to consider women's safety or unique responsibilities and travel patterns. And in medical research, women have largely been excluded from studies and textbooks, leaving them chronically misunderstood, mistreated, and misdiagnosed. Built on hundreds of studies in the United States, in the United Kingdom, and around the world, and written with energy, wit, and sparkling intelligence, this is a groundbreaking, highly readable exposé that will change the way you look at the world.