Bibliographic record
Abstract
Popular perception holds that employment stability declined towards the end of the twentieth century.However, most studies conclude that the proportion of long term jobs has remained remarkably stable over the last few decades.This study focuses on this discrepancy by tracking self-reported changes in Canadian employment durations over an extended period.This is done in order to reconcile popular perception with recent studies and nest the existing literature in a broader historical context.The study makes use of finite mixture decompositions on successive cohorts of employees starting from the 1950s to identify worker types within cohort-based distributions.Then, using tests of stochastic dominance, it is shown that the distribution of employment has indeed changed.Furthermore, detailed examination by employment spell and birth cohort is used to identify contributing factors to the identified declines in stability.It is surmised that structural changes in the economy and broader society played a large role in the seeming reduction in employment stability.While for men these shifts were clear, for women the evidence was more mixed.I owe my gratitude to a number of people and organizations who have helped make this work possible.First and foremost I'd like to thank my adviser, Professor Marcel Voia for giving me invaluable guidance over the past past six years.Not only has he helped in shaping the ideas that are contained in this document but he has encouraged me to explore new and fascinating ways to approach empirical research.It has been a great pleasure working with him.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".