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Counterwill, Defiance, and Emotional Safety in ADD: The Defiant Ones | Chapter 20 of Scattered Minds by Gabor Maté

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Counterwill, Defiance, and Emotional Safety in ADD: The Defiant Ones | Chapter 20 of Scattered Minds by Gabor Maté Welcome to Last Minute Lecture’s summary of Chapter 20 from Scattered Minds by Dr. Gabor Maté. In this chapter, Dr. Maté unpacks defiance and oppositionality in ADD children, revealing that “stubbornness” is often counterwill—a natural, protective response to feeling controlled, not a sign of willful disobedience. Watch our full chapter video below, and subscribe to Last Minute Lecture for more trauma-informed parenting guides and deep-dives into child psychology: Subscribe to Last Minute Lecture for more chapter-by-chapter textbook summaries and family support resources. Understanding Counterwill: Natural Resistance, Not Rebellion Dr. Maté introduces the concept of counterwill—a biologically-wired resistance to control or coercion. In ADD, this can manifest as verbal defiance, passive refusal, mood swings, and all-or-nothing thinking. Rather than being a ch...

Graph Algorithms Explained — BFS, DFS, Topological Sort & SCCs | Chapter 20 in Introduction to Algorithms

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Graph Algorithms Explained — BFS, DFS, Topological Sort & SCCs | Chapter 20 in Introduction to Algorithms Graph algorithms are at the heart of many critical operations in computer science, from web crawling and pathfinding to task scheduling and dependency resolution. Chapter 20 of Introduction to Algorithms (CLRS) provides a comprehensive overview of graph representations, traversal algorithms like BFS and DFS, and advanced applications such as topological sorting and strongly connected components (SCCs). Whether you're studying for AP Computer Science or brushing up on algorithm fundamentals, this chapter is essential reading. 📺 Watch the full video above for a visual breakdown of each algorithm and its application, or keep reading for an in-depth written explanation. Graph Representations Graphs can be represented in two main ways: adjacency lists and adjacency matrices. Each has trade-offs in space and time complexity depending on the graph’s density. Adja...