Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The first chapter studies the labour force participation of older individuals during COVID-19. COVID-19 significantly changed the labour participation rates of older Canadians, leading to substantial flows among employment, unemployment, marginal attachment, and non-attachment. Using the Canadian Labour Force Survey (LFS), this paper examines the impact of these flows on the participation rates of older individuals and explores whether COVID-19 prompted early retirements. Unlike the Great Recession, the pandemic caused significant direct separations from employment to non-participation. Additionally, older women experienced slower participation rate recovery than men due to higher outflows and lower inflows. Notably, many individuals who initially became non-attached to the labour force in early 2020 transitioned back to employment in the following months of the same year. Generally, the pandemic did not increase older individuals' self-reported retirement transitions and reduced their probability of staying non-attached to the labour market. The second chapter examines the cyclicality of worker flows across experience levels in Canada. Using the LFS, I estimate individual monthly transition probabilities over business cycles conditional on labour-market experience and job tenure. The job-finding rate and separation rate are relatively more cyclical for the youth. I find that experience is a major contributor to the cyclical fluctuations in employer-to-employer probabilities, whereas tenure is a major contributor to the cyclicality of employment-to-nonemployment. The third chapter studies the evolution of the gender unemployment gap in Canada. The gender unemployment gap - defined as women's unemployment rates minus men's unemployment rates - was positive before 1990 but has remained negative since then. I decompose the gender unemployment gap into contributions from gender differences in transition flows between employment, unemployment, and non-participation. The results show that gender differences in flows between employment and non-participation have been positive contributors to the gap over time, while gender differences in employment-to-unemployment flows have been a significant negative contributor. Over the decades, the contribution of flows between employment and non-participation has been decreasing. As employment-to-unemployment flows continue to contribute negatively to the gap, the diminishing contribution of flows between employment and non-participation explains the flip of the gender unemployment gap from positive to negative. Furthermore, I find that differences in industry and occupation composition play a significant role in explaining the gender difference in employment-to-unemployment transition rates.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it