DEPARTMENT OF ECONOMICS WORKING PAPER SERIES
Bibliographic record
Abstract
It is a widely held view that imperfect capital markets mean that individuals from poor backgrounds cannot borrow in order to finance educational investments. This view pervades policy formation, and is reflected in the fact that post-compulsory education processes in all countries involve considerable government intervention and large public subsidies. The evidence that credit constraints limit human capital investments is controversial. It is largely indirect or inferential, based, for example, on observed correlations between family income and the pursuit of post-secondary education. Other researchers have challenged the conclusions of such studies on several grounds. A balanced view may be that the importance of credit constraints to training and education choices is not yet resolved. This paper uses unique data to take a new approach to this question. Specifically, the 1995 Canadian Out of Employment Panel (COEP) allows us to explore the financial resources and skill formation choices of a large number of recent job losers. This approach has three advantages. First, it is a fairly direct investigation of the role of credit constraints. We have good measures of the financial resources of our subjects, in particular a measure of liquid assets or
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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 | 0.000 |
| 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) | 0.003 | 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".