The effect of information in the utilization of preventive health‐care strategies: An application to breast cancer
Bibliographic record
Abstract
This paper investigates the net benefit of mammography. A theoretical expected utility (EU) model shows that increases in breast cancer risk, decreases in false-negative and false-positive rates, decreases in cost and increases/decreases in quality of life with early/late-stage breast cancer increase the net benefit of mammography. The theoretical findings are tested in an empirical analysis using Canadian data. The empirical results are broadly consistent with the EU hypothesis. Results suggest that women at higher risk are more likely to obtain a mammogram. In particular, individuals are significantly more likely to have had a time-appropriate mammogram if the mother's cause of death was breast cancer, and if the sister had breast cancer. The results also show that older age (related to higher risk and more accurate mammograms) increases mammography use, and that decreases in time and opportunity costs, and better health behaviours generally have the same effect.
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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 | 0.000 |
| 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) | 0.000 | 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".