Explaining the Rise in Self-Employment: A Search Theoretic Approach
Bibliographic record
Abstract
Since the late 1970's the number self-employed as a proportion of total employment has increased by 48.6 % in Canada, rising from 10.9 % in 1976 to 16.2 % in 1996. In this paper, a search theoretic model that includes a self-employment sector is introduced. The model is then estimated using two Canadian longitudinal data sets, the Labour Market Activity Survey (LMAS) from 1988-1990 and the Survey of Labour and Income Dynamics (SLID) from 1994-1996. The estimates from the LMAS and SLID are compared to see what factors within the search theoretic framework can explain the increase in self-employment. The use of a structural model allows me to find results that have not been obtained in previous reduced form work. In particular, the parameters of the structural model provides evidence on why the flows in and out of self-employment have changed. The results reveal that the increased flow into self-employment from unemployment is not only caused by the lack of wage employment opportunities, but by an improvement in the prospective returns in self-employment and by an increase in individuals choosing to enter self-employment as an intermediate step between unemployment and wage-employment.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".