Demography, Population, and Ecology Commons^™

A Middle Ground: The Gendered Division Of Housework In Heterosexual Mixed-Nativity Couples, Rebecca Rayner

MA Research Paper

Little is known about how couples in mixed-nativity marriages divide household labor compared to their peers in mixed-nativity cohabitations. Using data from the Integrated Public Use Microdata (IPUMS) files of the American Time Use Survey, this paper asks: (1) how does the division of housework for heterosexual mixed-nativity couples, both married and cohabiting, compare to that of their same-nativity counterparts? and (2) how does the gendered division of housework for heterosexual cohabiting mixed-nativity couples differ from that of married mixed- nativity couples? Findings indicate that mixed-nativity unions operate as a “middle ground” between same-nativity unions. When stratifying by marital status, …

Early Adult Transitions In Canada: Expectations, Stability And Change, Laura Wright

Electronic Thesis and Dissertation Repository

The transition to adulthood is a much longer and less structured process for more recent generations than for those who came of age before the 1960s. Median age at first marriage has been increasing, cohabitation has become more prevalent, the role of cohabitation in the partnering process has changed, and young adults tend to live with their parents longer. This dissertation presents three studies of how new cohorts of Canadian youth are leaving home and starting their conjugal lives. I apply event history techniques using the 2011 General Social Survey, the most recent available data on the union and home-leaving …

Error In Demographic And Other Quantitative Data And Analyses, Thomas K. Burch Prof

Population Change and Lifecourse Strategic Knowledge Cluster Discussion Paper Series/ Un Réseau stratégique de connaissances Changements de population et parcours de vie Document de travail

This paper is about errors in statistical data. My remarks are in two parts. The first part deals with the proposition that the statistical data we consume, analyse and produce contain more error from more sources than we sometimes recognise. The second asks: How can we better deal with these errors?

The topic of error in statistics can become highly technical, but for the most part this is not a technical presentation. It deals with common sense and experience; much of it is anecdotal.