Bibliographic record
Abstract
This dissertation contains three essays on firm-sponsored training. Paper 1 develops a general theoretical framework in a frictional labour market to investigate how firms decide to sponsor how much general as well as specific training to workers assuming complementarity between the two types of training as well as education. It shows that firms’ profit maximizing decisions provide firms with an incentive to provide more training, general as well specific, to the more educated workers, more training for more educated workers may lead to low turnover rate, and the resulting life-time profile of firm-sponsored training is U-shaped or decreasing. The policy implications are that governments can subsidize both education and training to improve efficiency. Paper 2 and paper 3 try to provide empirical evidence from different perspectives, respectively determinants and effects of three types of firm-sponsored training, i.e., class-room training, on-the-job-training, and career-related but not job directly related training based on Statistics Canada’s Worker Place and Employee Survey (WES) of 2003/2004. The major empirical findings arising from our estimation results are: (1) Education is positively and significantly associated with the incidence of all three types of training, and significantly positively correlated with the intensity of on-the-job training. (2) Workers in larger firms are more likely to obtain classroom training and on-the-job training than workers in smaller firms. (3) Job tenure is significant and negative for the intensity of classroom training or on-the-job training. (4) Classroom-training and on-the-job training increases the average earnings of workers but less than average resultant firm-level productivity growth. Firm sponsored career related training has no significant impact on a worker’s earnings but increases the firm’s productivity significantly. All these findings by and large are consistent with the theory developed in first paper.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".