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| Rank-Size Rule× | Gravity Model of Migration× | |
|---|---|---|
| Lĩnh vực | Human Geography | Human Geography |
| Họ≠ | Process / pipeline | Regression model |
| Năm ra đời≠ | 1949 | 1946 |
| Người khởi xướng≠ | George Kingsley Zipf | George Kingsley Zipf (formalized); analogy to Newton's law of gravitation |
| Loại≠ | Empirical regularity and diagnostic for the size distribution of cities | Spatial-interaction regression model for migration flows |
| Công trình gốc≠ | Zipf, G. K. (1949). Human Behavior and the Principle of Least Effort. Addison-Wesley, Cambridge, MA. ISBN: 9781614273790 | Zipf, G. K. (1946). The P1 P2 / D hypothesis: On the intercity movement of persons. American Sociological Review, 11(6), 677–686. DOI ↗ |
| Tên gọi khác | Zipf's Law for Cities, Rank-Size Distribution, City-Size Rank-Size Relationship, Rank-Size Regularity | Migration Gravity Model, Demographic Gravity Model, Zipf P1P2/D Model, Gravity Model of Spatial Interaction (Migration) |
| Liên quan | 4 | 4 |
| Tóm tắt≠ | The rank-size rule is an empirical regularity describing the size distribution of cities within a country or region. In its simplest form, popularized by George Kingsley Zipf in 1949, the population of a city is inversely proportional to its rank, so the second-largest city is about half the size of the largest, the third about a third, and so on. Generalized to a power law with an exponent q, it provides a compact way to summarize how evenly or unevenly population is spread across a settlement system and to diagnose urban primacy. | The gravity model of migration explains the volume of movement between two places as proportional to the product of their populations (masses) and inversely proportional to the distance separating them, by direct analogy to Newton's law of universal gravitation. Formalized for intercity movement by George Kingsley Zipf in 1946 and embedded in regional science by Walter Isard, it is the workhorse model of human geography for predicting migration, commuting, and other spatial-interaction flows. |
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