Personal finances of residents at three Canadian universities.
Bibliographic record
Abstract
OBJECTIVES: To address 3 research questions (What financial choices do residents make? Are the financial choices of residents similar to those of the general public? Are the financial choices of surgical residents reasonable?), we examined financial data from Canadian residents. METHODS: A written survey was administered to 338 residents (103 of them surgical residents) at 3 Canadian training institutions (University of Toronto, Queen's University and University of Manitoba). Resident household cash flows, assets and liabilities were characterized. Finances for residents were compared with those of the general public, by means of the Survey of Household Spending and Survey of Financial Security. RESULTS: Median resident income was 45,000 dollars annually (Can dollars throughout). With a working spouse, median household income was 87,500 dollars. Among residents, 62% had educational debt (median 37,500 dollars), 39% maintained unpaid credit-card balances (median 1750 dollars), 36% did not budget expenses, 25% maintained cash reserves <275 dollars, and 22% contributed neither to retirement nor nonretirement investments. Residents spent more on vehicles compared with members of the general public (median 17,500 dollars v. 10,720 dollars, p = 0.002) and on monthly housing (median 875 dollars v. 729 dollars, p < 0.001), respectively. Residents were more likely to carry student loans than people in the general population (61% v. 21%), more likely to carry vehicle loans (74% v. 29%) and less likely to carry credit-card debts (39% v. 50%, respectively). Surgical residents had income expectations after graduation higher than current billings justified. Fewer surgical (69%) than anesthesiology residents (88%, p < 0.05) contributed to Registered Retirement Savings Plans. CONCLUSIONS: From this limited sample, residents spend more than age- and income-matched members of the general public. Many residents save too little, fail to budget, and carry high educational and credit-card debts. Surgical residents' expectations of future income may be unrealistic. Further study is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".