Canada has been active in attracting highly-skilled, foreign-trained workers to overcome its labour shortage, facilitate its economic growth, and enhance its global competency. While promoting gender equality in the workplace and advancing women’s labour market participation are ongoing focuses of Canada’s attention, the arrival of an increased number of skilled immigrant women and their marginalized experiences in the Canadian labour market reflects a critical problem that the underuse of highly skilled immigrant women’s professional skills might be a loss for both Canada and individual immigrants.
This research reveals the lived experience of highly skilled Chinese immigrant women in the Canadian labour market, and analyzes how the barriers to their career restoration were constructed. It adopts Seyla Benhabib’s weak version of postmodern feminist theory and Dorothy Smith’s Institutional Ethnography methodology. Based on interview data with 46 highly skilled Chinese immigrant women, this research identifies these immigrant women’s standpoint within the institutional arrangements and understands the barriers to their career restoration as discursively constructed outcomes. This research contends that the settlement services for new immigrants funded by the federal government fall short of meeting the particular needs of highly skilled immigrants who intend to find highly skilled jobs that match their qualifications. This research also makes recommendations for improving existing language training and employment-related settlement services in order to better assist highly skilled immigrants in using their skills to a larger extent.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/42505 |
| Date | 09 August 2021 |
| Creators | Wang, Chen |
| Contributors | Cameron, Angela, Liew, Jamie Chai Yun |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
Page generated in 0.0018 seconds