Fairly Equal

An eyewitness account of the revolution in women’s rights under the law. Lawyer, activist, and former Chatelaine legal columnist Linda Silver Dranoff details her own trailblazing journey from a traditional 1950s childhood to the battlegrounds of the courts of law and the halls of power where she and a generation of women lawyers, supporting a larger feminist movement, championed the rights of Canadian women and families. Through a combination of memoir and social history, Dranoff brings to life the struggles around family law, pay and employment equity, violence against women, abortion rights, childcare, pension rights, political engagement, public policy, and access to legal justice. From backroom battles to public and private protest, the stories are inspiring. Fairly Equal reminds us of the importance of remaining vigilant about our rights. Knowing what Dranoff’s generation of women lawyers and activists achieved, and how easily it can be taken away, we are encouraged in sisterhood and solidarity to ensure that the many hard-won gains of the feminist movement are maintained and expanded for the women who follow.

Compensation fairness is a universal preoccupation in today’s workplace, from whispers around the water cooler to kabuki in the C-suite. Gender discrimination takes center stage in discussions of internal pay equity, but many other protected characteristics may be invoked as grounds for alleging discrimination: age, race, disability, physical appearance, and more. This broad range of vulnerability to discrimination charges is often neglected in corporate assessments of how well compensation systems comply with the law and satisfy employee norms of fairness. Blind spots in general equity constitute a serious threat to organizational performance and risk management. In Compensating Your Employees Fairly, a respected practitioner and consultant lays out in practical terms everything you need to know to protect your company along the full spectrum of internal pay equity issues, including all the technical methods you need to optimize compliance and minimize risk. Compensating Your Employees Fairly is a timely survey and comprehensive handbook for compensation specialists, HR professionals, EEO compliance officers, and in-house counsel. It provides all the information you need to ensure that compensation systems are equitable, auditable, internally consistent, and externally compliant with equal employment opportunity laws and regulations. The author presents technical information—both legal and statistical—in common-sense terms. Her non-technical breakdown of complex statistical concepts distills just as much as practitioners need to know in order to effectively deploy and interpret the standard applications of statistical analysis to internal pay equity. The focus throughout the book is on real-world application, current examples, and up-to-the-minute information on recent and pending wrinkles in the evolving legal landscape. Readers of Compensating Your Employees Fairly will learn: Why internal equity in compensation matters How to detect intentional and non-intentional discrimination in compensation The basics of statistical inference and multiple regression analysis The essentials of data availability, measurability, and collection The criteria for assessing compensation systems for internal equity How to investigate potential problems and react to formal complaints and actions How to avoid litigation and put in place ongoing measures for proactive self-auditing

Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

Vols. 39-214 (1874/75-1921/22) have a section 2 containing "Other selected papers"; issued separately, 1923-35, as the institution's Selected engineering papers.