Analysis of the Growth and Shift in Sectoral Part-time Employment in Canada 1987-1999
Bibliographic record
Abstract
Aggregate employment data mask some profound trends in the performance of the economy. The overall performance of the national economy is the result of overall economic performance of the sub-national economies. Therefore, a thorough understanding of the changing pattern of industrial activity at the provincial level, and hence the changing composition of employment, vis-a-vis part-time employment across the provinces is vitally important. Consequently in this study we endeavor to analyze and delineate the changes in part-time employment pattern of the provincial economies in the past decade. A modified version of the ShiftShare model, as developed by Stilwell [1969], is used for an in-depth analysis of recently available 15 sectoral classification of employment data which include some sectors of the knowledge based economy. The first section describes th e m ethodology, ai ms an d sh ortcomings of the Sh ift-Share technique. The second section specifies the modified version of the model. The results are presented in the third section and finally the conclusions of the study are presented.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".