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Lone-parent Families (lone-parent + family)

Distribution by Scientific Domains
Humanities and Social Sciences100%

Selected Abstracts

Children's Perceptions of Families: What Do They Really Think?

CHILDREN & SOCIETY, Issue 1 2007
Andrea Rigg
The perceptions of 111 New Zealand children from different family structures and cultures were examined. Lone-parent families, blended families, extended family, non-residential parents and couples with children were highly endorsed. No great distinctions were made between married and cohabiting couples when the relationship included children. Definitions of family frequently mentioned affective factors. In comparing ethnic groups and family structures some differences were noted, but in general children have many similarities in their family concepts. Comparisons with a recent study of adolescents did not reveal clear-cut developmental sequences in young people's perceptions. Overall, an inclusive and realistic view of families was expressed. © 2006 The Author(s) Journal compilation © 2006 National Children's Bureau. [source]

Making work pay, making tax credits work: An assessment with specific reference to lone-parent employment

INTERNATIONAL SOCIAL SECURITY REVIEW, Issue 2 2008
Jane Millar
Abstract This article examines the origins, aims, and design of tax credits in the United Kingdom, and discusses the extent to which tax credits represent a new approach in social security policy. It then focuses on the role that these transfers play in supporting lone mothers in employment, drawing on the experiences of lone-parent families to explore how tax credits worked for them. The discussion highlights the tensions between family and employment change and tax credits rules about reporting changes in circumstances and income. [source]

Modélisation spatiale de la pauvretéà Montréal: apport méthodologique de la régression géographiquement pondérée

THE CANADIAN GEOGRAPHER/LE GEOGRAPHE CANADIEN, Issue 4 2007
PHILIPPE APPARICIO
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, L'île de Montréal est particulièrement touchée par la pauvreté, puisqu'en 2000 29 pour cent de sa population vivait sous le seuil de faible revenu tel que défini par Statistique Canada. La pauvreté ne constituant pas toutefois un phénomène homogène à l'échelle intra-urbaine, l'identification et la qualification des zones de pauvreté deviennent des enjeux de recherche de première importance. Dans cette perspective, cet article propose une analyse des facteurs qui déterminent la distribution spatiale de la pauvreté au niveau des secteurs de recensement de l'île de Montréal. Pour ce faire, l'analyse mobilise un outil méthodologique particulier: la régression géographiquement pondérée, et en compare les résultats avec un modèle de régression multiple global. Au niveau global, on constate que les facteurs classiques conduisant à la pauvreté sont à l',uvre sur le territoire de l'île de Montréal. Dans l'ordre, ces facteurs sont: le chômage, la monoparentalité, le fait de vivre seul, le fait d'être un immigrant récent, le travail atypique et la non-fréquentation scolaire des jeunes de 15 à 24 ans. Au niveau local, s'il est vrai we observe that variables employment and lone-parents families play significantly in almost all the census tracts, the four other factors are significant only in some census tracts in the center of the Island. At the end of this analysis, the advantages of the GWR methodology appear clearly, as its capacity to take into account the geographical variations of the phenomenon allows a better identification and categorization of poverty areas in Montréal. que le chômage et la monoparentalité agissent significativement dans presque tous les secteurs, les quatre autres facteurs sont uniquement significatifs dans certains secteurs du centre de l'île. Au terme de l'analyse, les avantages de la régression géographiquement pondérée apparaissent clairement, sa plus grande sensibilité aux variations spatiales du phénomène permettant de mieux identifier et qualifier les zones de pauvreté montréalaises. [source]

Socio-genealogical connectedness: on the role of gender and same-gender parenting in mitigating the effects of parental divorce

CHILD & FAMILY SOCIAL WORK, Issue 2 2000
Owusu-Bempah
Guided by the idea of socio-genealogical connectedness (i.e. knowledge, and belief in, one's biological and social roots), the present study explored the relationship between a number of the characteristics of lone-parent families and the well-being of children in these families. Since it is well established that develop-mental difficulties do not emerge in all children of divorced/separated families, there is a need to understand those factors which mitigate against the adverse influences of divorce on children. Evidence suggests that socio-genealogical connectedness is one of the possible mitigating factors. However, the present study, which involved a variety of multivariate statistical techniques, indicates academic attainment to be the most important mitigating factor. This implies that children with greater intellectual resources to deal with problems are less vulnerable than others to the long-term effects of divorce and separation. Nonetheless, the results support the hypothesis derived from the concept of socio-genealogical connectedness; it was the second most important predictor. [source]

Modélisation spatiale de la pauvretéà Montréal: apport méthodologique de la régression géographiquement pondérée

THE CANADIAN GEOGRAPHER/LE GEOGRAPHE CANADIEN, Issue 4 2007
PHILIPPE APPARICIO
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, L'île de Montréal est particulièrement touchée par la pauvreté, puisqu'en 2000 29 pour cent de sa population vivait sous le seuil de faible revenu tel que défini par Statistique Canada. La pauvreté ne constituant pas toutefois un phénomène homogène à l'échelle intra-urbaine, l'identification et la qualification des zones de pauvreté deviennent des enjeux de recherche de première importance. Dans cette perspective, cet article propose une analyse des facteurs qui déterminent la distribution spatiale de la pauvreté au niveau des secteurs de recensement de l'île de Montréal. Pour ce faire, l'analyse mobilise un outil méthodologique particulier: la régression géographiquement pondérée, et en compare les résultats avec un modèle de régression multiple global. Au niveau global, on constate que les facteurs classiques conduisant à la pauvreté sont à l',uvre sur le territoire de l'île de Montréal. Dans l'ordre, ces facteurs sont: le chômage, la monoparentalité, le fait de vivre seul, le fait d'être un immigrant récent, le travail atypique et la non-fréquentation scolaire des jeunes de 15 à 24 ans. Au niveau local, s'il est vrai we observe that variables employment and lone-parents families play significantly in almost all the census tracts, the four other factors are significant only in some census tracts in the center of the Island. At the end of this analysis, the advantages of the GWR methodology appear clearly, as its capacity to take into account the geographical variations of the phenomenon allows a better identification and categorization of poverty areas in Montréal. que le chômage et la monoparentalité agissent significativement dans presque tous les secteurs, les quatre autres facteurs sont uniquement significatifs dans certains secteurs du centre de l'île. Au terme de l'analyse, les avantages de la régression géographiquement pondérée apparaissent clairement, sa plus grande sensibilité aux variations spatiales du phénomène permettant de mieux identifier et qualifier les zones de pauvreté montréalaises. [source]