Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it