Essays on job loss and social stratification in Canada and the United States
Bibliographic record
Abstract
Job loss is an ever-present feature of North American labor markets. Each year, employers eliminate positions, close down branches, or even go out of business as part of routine business decisions. In recent decades, even in times of economic expansion rates of job loss have persisted across a wide range of demographic and labor market groups. This dissertation examines the fluctuations in life people face after losing a job in Canada and the United States. In the first paper I study the relationship between job loss and geographic mobility in Canada. Moving is one way individuals may respond to being laid off, either to relocate to cheaper housing or in search of work. Using data from the 1996-2010 Survey of Labour and Income Dynamics, I find that job loss is associated with both short-distance residential mobility and long-distance migration, and triggers selective neighborhood mobility. The findings establish job loss as a key life course transition motivating residential mobility and long-distance migration in Canada, and as an event that initiates entry into high poverty neighborhoods.The second paper explores to what extent job loss triggers geographic mobility in the United States in the period leading up to the Great Recession. Drawing on geocoded data from the 2003-2007 Panel Study of Income Dynamics, I find that being laid off increases the likelihood of both short- and long-distance moves. Job loss also interrupts the housing career: individuals who lose a job are more than twice as likely as people who remain stably employed to transition from owning to renting a home. For those who began as renters, job loss is associated with a decreased likelihood of making a move into homeownership. Finally, being laid off is associated with selection into a high-poverty census tract for those who lived in a lower poverty tract in the previous wave. The third and final paper examines the short-term income trajectories of displaced workers in the U.S. and Canada. Using data from the 1996-2012 U.S. Survey of Income and Program Participation and Canadian Survey of Labour and Income Dynamics I assess to what extent displaced workers experience changes in four important measures of financial well-being: earnings, individual income, pre-tax and transfer household income, and after-tax and transfer household income. Comparing these income sources elucidates the role of labor markets, families, and social safety net programs in determining income mobility following job loss. Results show that in both countries displaced workers experience earnings losses. I further find that total household income falls following displacement, but this deterioration is mitigated by receipt of transfer payments. While the post-tax and transfer income losses in the two countries are similar, the welfare state plays a larger role of replacing income in Canada, as individuals experience larger earnings losses.Taken together, this research elucidates the social and economic consequences of job loss in North America. The first two papers provide novel evidence on the range of geographic mobility people undertake following a job loss by considering not only long-distance migration but also short-distance residential mobility and the outcomes of moves, including exposure to neighborhood poverty and transitions in homeownership. The results indicate that many moves are undertaken locally and often involve losing out on neighborhood quality or homeownership, which may ultimately compound the financial hardships associated with job loss. The third paper is one of the first to evaluate the economic consequences of job displacement, specifically, in comparative perspective. In doing so, I demonstrate how national institutions shape the experience of job loss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.034 | 0.010 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".