Demography, Population, and Ecology Commons^™

The Transformation Of Conjugal Partnerships: Union Transitions And Trajectories In Canada, Ching Jiangqin Du

Electronic Thesis and Dissertation Repository

Conjugal partnerships have undergone unprecedented changes in Canadathroughout the past several decades, especially with regard to the flexibility in entry and exit from intimate relationships. The development of longitudinal datasets and advanced methods further facilitates analyses of partnership transformations from a life-course theoretical perspective and in a wide analytical scope. This dissertation investigates partnership transformations in Canadaby examining conjugal partnership trajectories and by exploring the risk factors associated with these partnership transformations.

Employing dynamic analytical approaches (e.g., LIFEHIST analysis and survival analysis), this dissertation examines data from the retrospective General Social Survey (GSS) on Family Transitions, conducted by Statistics Canada …

Informality And Labor Market Dynamics During Economic Downturns: Evidence From Egypt, Rania Roushdy, May Gadallah

Poverty, Gender, and Youth

This working paper investigates the evolution of the Egyptian labor market during the world financial crisis period. There has been a mild decline in unemployment, combined with a slight increase in both labor force participation and employment to population ratio. Some subgroups of workers have been more vulnerable than others during the crisis period. The results of this paper concur with the historical experience, which suggests that young, old, unskilled and female workers are more likely to bear the brunt of an economic downturn.

Demographic Prediction Of Mobile User From Phone Usage, Shahram Mohrehkesh, Shuiwang Ji, Tamer Nadeem, Michele C. Weigle

Computer Science Faculty Publications

In this paper, we describe how we use the mobile phone usage of users to predict their demographic attributes. Using call log, visited GSM cells information, visited Bluetooth devices, visited Wireless LAN devices, accelerometer data, and so on, we predict the gender, age, marital status, job and number of people in household of users. The accuracy of developed classifiers for these classification problems ranges from 45-87% depending upon the particular classification problem.