Bibliographic record
Abstract
Longobardi and colleagues examined the effect of inflammatory bowel disease (IBD) on employment, using data from 10,891 respondents aged 20 to 64 years from the 1998 cycle of the Canadian National Population Health Survey (NPHS) (1). This sample included 187 (1.7%) subjects who self‐reported IBD or a similar bowel disorder. A significantly greater proportion of IBD than non‐IBD respondents reported that they were not in the labour force (28.9% versus 18.5%). Even after adjusting for other factors (age group, level of pain, etc), subjects with IBD had a 2.9% higher nonparticipation rate (21.4%). For example, among people not hospitalized within the past year and with no limitation of activities due to pain, IBD subjects were 1.2 times more likely to be unemployed than those without IBD. Subjects who reported high levels of pain had a very high probability of being out of the labour force. Based on Canadian annual compensation data for all employed persons in Canada, and age‐ and sex‐specific prevalence, and incidence rates for IBD, the authors estimated that there are 119,980 IBD patients between the ages of 20 and 64 years in Canada and that this group includes 3479 people who are not in the labour force. This translates into lost wages of $104.2 million, or $868 per IBD patient
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".