PovertyPoverty is a state or condition in which one lacks the financial resources and essentials for a certain standard of living. Poverty can have diverse social, economic, and political causes and effects. When evaluating poverty in statistics or economics there are two main measures: absolute poverty compares income against the amount needed to meet basic personal needs, such as food, clothing, and shelter; relative poverty measures when a person cannot meet a minimum level of living standards, compared to others in the same time and place.
Cycle of povertyIn economics, a cycle of poverty or poverty trap is caused by self-reinforcing mechanisms that cause poverty, once it exists, to persist unless there is outside intervention. It can persist across generations, and when applied to developing countries, is also known as a development trap. Families trapped in the cycle of poverty have few to no resources. There are many self-reinforcing disadvantages that make it virtually impossible for individuals to break the cycle.
Poverty reductionPoverty reduction, poverty relief, or poverty alleviation is a set of measures, both economic and humanitarian, that are intended to permanently lift people out of poverty. Measures, like those promoted by Henry George in his economics classic Progress and Poverty, are those that raise, or are intended to raise, ways of enabling the poor to create wealth for themselves as a conduit of ending poverty forever. In modern times, various economists within the Georgism movement propose measures like the land value tax to enhance access to the natural world for all.
Space complexityThe space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely. This includes the memory space used by its inputs, called input space, and any other (auxiliary) memory it uses during execution, which is called auxiliary space. Similar to time complexity, space complexity is often expressed asymptotically in big O notation, such as etc.
Parameterized complexityIn computer science, parameterized complexity is a branch of computational complexity theory that focuses on classifying computational problems according to their inherent difficulty with respect to multiple parameters of the input or output. The complexity of a problem is then measured as a function of those parameters. This allows the classification of NP-hard problems on a finer scale than in the classical setting, where the complexity of a problem is only measured as a function of the number of bits in the input.
