Bibliographic record
Abstract
The study examines long-term effects of cancer on the work status and annual earnings of cancer survivors who had a strong attachment to the labor market prior to their cancer diagnosis. We use linkage data combining Canadian 1991 Census microdata with administrative records from the Canadian Cancer Registry, the Vital Statistics Registry and longitudinal personal income tax records. We estimate changes in the magnitude of cancer effects during the first 3 years following the year of the diagnosis using a large sample of cancer survivors diagnosed at ages 25 to 61. The comparison group consists of similar workers never diagnosed with cancer. The empirical strategy combines coarsened exact matching and regression models to deal with observed and unobserved differences between the cancer and comparison groups. The results show moderate negative cancer effects on work status and annual earnings. Over the 3-year period following the year of the diagnosis, the probability of working is 5 percentage points lower for cancer survivors than for the comparison group, and their earnings are 10% lower. Our findings also suggest that the effects of cancer on labor market outcomes differ for high and low survival rate cancer categories. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".