Wages For Housework

A history of the feminist movement that changed how we see women's work forever

Compilation of documents and texts from The New York Wages for Housework Committee 1972-1977 and from other branches of the Wages for Housework movement.

Annotation This book is a history of housework in the United States prior to the Civil War. More particularly, it is a history of women's unpaid domestic labour in the context of the emergence of an industrialized society in the northern United States.

The Problem with Work develops a Marxist feminist critique of the structures and ethics of work, as well as a perspective for imagining a life no longer subordinated to them.

At a time when we are witnessing a worldwide expansion of capitalist relations, a feminist rethinking of Marx’s work is vitally important. In Patriarchy of the Wage, Silvia Federici, bestselling author and the most important Marxist feminist of our era, asks why Marx's crucial analysis of the exploitation of human labor was blind to women’s work and struggle on the terrain of social reproduction. Why was Marx unable to anticipate the profound transformations in the proletarian family that took place at the turn of the nineteenth century creating a new patriarchal regime? Patriarchy of the Wage does more than just redefine classical Marxism. It is an urgent call for a new kind of radical politics.

A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

Today all politics are reproductive politics, argues esteemed feminist critic Laura Briggs. From longer work hours to the election of Donald Trump, our current political crisis is above all about reproduction. Households are where we face our economic realities as social safety nets get cut and wages decline. Briggs brilliantly outlines how politicians’ racist accounts of reproduction—stories of Black “welfare queens” and Latina “breeding machines"—were the leading wedge in the government and business disinvestment in families. With decreasing wages, rising McJobs, and no resources for family care, our households have grown ever more precarious over the past forty years in sharply race-and class-stratified ways. This crisis, argues Briggs, fuels all others—from immigration to gay marriage, anti-feminism to the rise of the Tea Party.