A definitive history of consumer activism, Buying Power traces the lineage of this political tradition back to our nation’s founding, revealing that Americans used purchasing power to support causes and punish enemies long before the word boycott even entered our lexicon. Taking the Boston Tea Party as his starting point, Lawrence Glickman argues that the rejection of British imports by revolutionary patriots inaugurated a continuous series of consumer boycotts, campaigns for safe and ethical consumption, and efforts to make goods more broadly accessible. He explores abolitionist-led efforts to eschew slave-made goods, African American consumer campaigns against Jim Crow, a 1930s refusal of silk from fascist Japan, and emerging contemporary movements like slow food. Uncovering previously unknown episodes and analyzing famous events from a fresh perspective, Glickman illuminates moments when consumer activism intersected with political and civil rights movements. He also sheds new light on activists’ relationship with the consumer movement, which gave rise to lobbies like the National Consumers League and Consumers Union as well as ill-fated legislation to create a federal Consumer Protection Agency.

This Palgrave Pivot offers a history of and proof against claims of "buying power" and the impact this myth has had on understanding media, race, class and economics in the United States. For generations Black people have been told they have what is now said to be more than one trillion dollars of "buying power," and this book argues that commentators have misused this claim largely to blame Black communities for their own poverty based on squandered economic opportunity. This book exposes the claim as both a marketing strategy and myth, while also showing how that myth functions simultaneously as a case study for propaganda and commercial media coverage of economics. In sum, while “buying power” is indeed an economic and marketing phrase applied to any number of racial, ethnic, religious, gender, age or group of consumers, it has a specific application to Black America.

Eager to change the world? Learn how you can have a greater social impact through your everyday purchases. The money we routinely spend on food, clothes, gifts, and even indulgences is an untapped superpower. What would happen if we slowed down to make more thoughtful decisions about what we buy? For "mom and pop" stores across the country, and artisan and agricultural communities around the world, every purchase matters. Consumers--whether individuals, small businesses, or corporations--are paying more attention than ever to how their goods are made; and retailers--large and small--are responding by investing in ethical and eco-friendly production. Yet figuring out which brands to support can feel overwhelming. Jane Mosbacher Morris has devoted her career to creating economic opportunities for vulnerable communities around the world, and in this valuable book, she shares her passion and insights on how we, as consumers, can create positive change too. Covering topics that range from why not all factories are evil, to how our morning coffee can be the easiest way for us to use our purchasing power for good, Buy the Change You Want to See makes us better informed consumers. Morris tells inspiring stories about how victims of human trafficking and natural disasters have been empowered by economic opportunity, and she offers practical ideas about how we can support these communities through our purchases--whether it comes to jewelry made from recycled materials in Haiti, sustainably grown and ethically sourced coffee and chocolate from farmers in some of the poorest regions of the world, or mass-produced jeans and shoes made in factories where workers are guaranteed decent working conditions and a fair wage.

"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a

Why do Canadians consume? This book explores the meanings of consumption in early-twentieth-century Canada, demonstrating that many Canadians have long viewed consumer goods as central to their visions of belonging, identity, and citizenship.

The Qing dynasty office purchase system (juanna), which allowed individuals to pay for government appointments, was regarded in traditional Chinese historiography as inherently corrupt and anti-meritocratic. Lawrence Zhang's groundbreaking study of a broad selection of new archival and other printed evidence contradicts this widely held assessment.