TRENDS IN MANUFACTURING EMPLOYMENT
Bibliographic record
Abstract
The challenges experienced by Canadian manufacturers in the past few years are a subject of public policy interest (Industry Canada 2007). These challenges have very real effects on the economy. From 2004 to 2008, more than one in seven manufacturing jobs, nearly 322,000, disappeared. In some regions of the country where the economy is not very diversified, the loss of manufacturing jobs can have particularly negative effects. In these regions, the closure of even a single plant, supplied by several companies, can weaken the economy. At the same time, job growth in other industries has been relatively strong. In fact, from 2004 to 2008, over 1.5 million jobs were created in the rest of the economy—a growth of 11%. The national unemployment rate through 2007 and 2008 was also regularly among the lowest in the past 30 years. Manufacturing is clearly faring worse than the rest of the economy. This study paints a detailed picture of employment trends in manufacturing in Canada from 1998 to 2008. Most of the data are from the Labour Force Survey (LFS) (see Data source and definitions).
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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 | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".