Bibliographic record
Abstract
he term "precarious employment" has become part of the lexicon of academics, the media and a growing number of politicians at the municipal, provincial and federal levels.Almost daily we hear in the media of the frustration of workers unable to find decent paying, permanent employment and having to accept temporary positions with few benefits beyond a wage.This lack of employment stability affects young adults wanting to start their own families, immigrants hoping to start a new life in Canada, parents eager to see their children launch their own careers, and workers displaced from secure jobs and needing to start over.These frustrations are fueling a growing sense of public unease and a sense that something is wrong with a labour market that amply rewards a few, but leaves the majority of Canadians facing growing employment and income insecurity, low wages and uncertain career paths.The spread of precarious employment in Canada and elsewhere is well documented by researchers (See Vosko 2006;2010) as are its effects on the health of individual workers (See Quinlan and Bohle 2008;2009;Underhill and Quinlan 2011; Vives et.al.2013;Lewchuk, Clarke and de Wolff 2013).It is now linked to the emergence of a new underclass (Standing 2011).However, we are only beginning to fully understand the broader social implications of the spread of precarious employment and how it is reshaping households and communities (Carnoy 2000).The 2007 United Way Toronto (UWT) report, Losing Ground: The Persistent Growth of Family Poverty in Canada's Largest City, raised concerns about precarious employment's wider social effects.Under UWT leadership, a group of researchers and community and union activists began meeting in 2008 to develop a strategy to deepen our understanding of how the changing nature of Canadian labour markets was reshaping our communities.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".