“LEARN AS WE LEAD”: LESSONS FROM THE FRONT LINES OF THE POOR PEOPLE’S CAMPAIGN

Abstract

In the spring of 1968, over six thousand poor people—black, chicano, white, Puerto Rican, and Native American from rural areas to urban centers—converged on Washington, D.C. to call attention to poverty and inequality in the wealthiest and most powerful nation in the world. This six-week demonstration was part of Rev. Dr. Martin Luther King Jr.’s final and oft-forgotten Poor People’s Campaign. Fifty years later, thousands of people in over forty states have taken part in reviving this movement as the Poor People’s Campaign: A National Call for Moral Revival (PPC 2018+), co-chaired by Bishop William Barber and Rev. Dr. Liz Theoharis. From low-wage workers’ fight for $15/hour minimum wage in the South to the Apache struggle to protect sacred land from copper mining in Oak Flat, Arizona; from the battle to stop emergency managers from poisoning and privatizing water services in Michigan to the urgent demands to abolish the criminalization of black, immigrant, and poor communities, “Learn as We Lead” investigates how local and national organizers are utilizing the vehicle of the campaign to build a broad-based movement across lines of identity, geography, and issue, while centering the leadership of the poor. Drawing on participant observation within the campaign, interviews with over forty grassroots leaders from twenty-seven states, and archival research, this dissertation uncovers how movement practitioners are reproducing and reformulating a long history of multiracial and multi-issue class politics—from the welfare rights movement of the 1960s and 1970s to the National Union of the Homeless of the 1980s and 1990s, from the Poor People’s Economic Human Rights Campaign (PPEHRC) of the early 2000s to the Moral Mondays and low-wage worker movements of recent years. In a time of deepening political, economic, environmental and health crisis, leaders with the PPC 2018+ offer critical insights on forging class consciousness and solidarity across difference.