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Input-Output Analysis is a quantitative economic technique that represents the interdependencies between different sectors of a national economy or different regional economies. It helps in understanding how changes in one industry can affect others, thereby aiding in economic planning and policy-making.
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Systems theory is an interdisciplinary framework that analyzes complex entities as cohesive, interconnected wholes rather than isolated parts. It emphasizes the interdependence of components and the dynamic interactions within systems, applicable across various fields such as biology, engineering, and social sciences.
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Causality refers to the relationship between causes and effects, where one event (the cause) directly influences the occurrence of another event (the effect). Understanding causality is crucial in fields such as science, philosophy, and statistics, as it allows for the prediction, explanation, and manipulation of phenomena.
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Opacity refers to the degree to which a material or surface prevents the passage of light, making it a crucial factor in fields like optics, material science, and privacy design. It is often contrasted with transparency and translucency, and its measurement is vital in applications ranging from computer graphics to environmental science.
Machine Learning Interpretability is crucial for understanding and trusting the decisions made by complex models, especially in high-stakes domains like healthcare and finance. It involves techniques and tools that make the model's predictions understandable to humans, ensuring transparency and accountability.
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Functional abstraction is like a magic box that helps you do things without knowing all the tiny details inside. It makes it easier to solve big problems by using simple instructions, just like how you use a remote control to turn on the TV without understanding how it works inside.
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Complex systems are characterized by intricate interactions and interdependencies among their components, leading to emergent behavior that cannot be easily predicted from the properties of individual parts. These systems are often adaptive, dynamic, and exhibit non-linear behaviors, making them challenging to analyze and manage.
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Cybernetics is an interdisciplinary field focused on the study of systems, control, and communication in animals, machines, and organizations. It emphasizes feedback loops, self-regulation, and the interconnectivity of components to understand complex systems and improve their functionality.
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Actor-Network Theory (ANT) is a sociological framework that explores the interconnectedness of human and non-human entities, emphasizing their equal agency in shaping social phenomena. It challenges traditional distinctions between society and technology, suggesting that networks of relationships, rather than individual actors, drive social dynamics.
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