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Modélisation spatiale de la pauvretéà Montréal: apport méthodologique de la régression géographiquement pondérée
Author(s) -
APPARICIO PHILIPPE,
SÉGUIN ANNEMARIE,
LELOUP XAVIER
Publication year - 2007
Publication title -
the canadian geographer / le géographe canadien
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.35
H-Index - 46
eISSN - 1541-0064
pISSN - 0008-3658
DOI - 10.1111/j.1541-0064.2007.00189.x
Subject(s) - poverty , geographically weighted regression , homogeneous , geography , unemployment , phenomenon , immigration , sociology , regional science , statistics , economics , mathematics , economic growth , combinatorics , physics , archaeology , quantum mechanics
Spatial Modeling of Poverty in Montréal: Methodological Contribution of the Geographically Weighted Regression The Island of Montréal is particularly concerned with the issue of poverty. In 2000, 29 percent of its inhabitants lived under the low income cut‐offs as defined by Statistics Canada. However, poverty is not a homogeneous phenomenon at the intra‐urban scale, and identifying and categorizing spaces of poverty has become a main concern for ongoing researches. According to this way of thinking, this paper proposes an analysis of the factors influencing the geographical distribution of poverty on the Island of Montréal. To be able to identify properly the various profiles of poverty, this analysis uses a specific methodology, the geographically weighted regression (GWR), and compares its results with the ones of a classical regression model. At the global level, the most important factors to explain poverty are in order: unemployment, lone‐parent families, one person households, recent immigrants, part time or part year workers, school dropouts. At the local level ,