The Shifting Geography of Precarious Employment in Canada
Bibliographic record
Abstract
This thesis marks an attempt to define and pinpoint a critical geography of precarious employment in Canada, which has garnered little attention thus far. In doing so, it provides the first detailed analysis of the geographic and temporal dimensions (across provinces, economic regions and census divisions) of precarious employment in Canada. To study these trends, the thesis draws on data from the Labour Force Survey (LFS) and the Canadian Census of Population. The LFS is used to determine long-term national- and provincial- level trends of precarious employment from 1976 to 2013, while the census is used to provide a clearer snapshot of the geographical dimensions of precarious employment in Canada for the years 1991 to 2011. Using the Moran’s I test and local indicators of spatial association (LISA), I discover that different forms of precarious employment exhibit distinct spatiotemporal patterns. With special attention placed on youth employment trends, I find that shifts in the spatial clustering of precarious employment indicators for the total labour force tend to mirror shifts experienced by young workers, only they occurred several years later for the total labour force. This pattern suggests that young people are more susceptible to changes in labour market dynamics.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".