Which Fields Pay, Which Fields Don't? An Examination of the Returns to University Education in Canada by Detailed Field of Study
Bibliographic record
Abstract
The decision to attend university has a significant impact on an individual’s lifetime earnings, as does his choice of field of study and whether or not to pursue graduate studies. This paper uses data from the 1996 Canadian Census to compute estimates of the private rate of return associated with these choices. Use of data from the full (20 per cent) sample allows for estimates to be computed by detailed field of study. We find that the heterogeneity in rates of return across major fields of study documented in previous research is found to persist within more narrowly defined fields of study. We find rates of return to bachelor’s degrees to be positive for all detailed fields of study; thus, they represent a sound investment. The same holds true for the vast majority of individuals pursuing graduate degrees. Additionally, use of 2002-03 tuition fee data indicates that recent increases in tuition fees has a noticeable, but not overwhelming, impact on rates of return; no field that was profitable under the 1995-96 cost structure is rendered unprofitable despite substantial increases in costs.
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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 | 0.001 | 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) | 0.000 | 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".