Cohort Profile: The Interdisciplinary Study of Inequalities in Smoking (ISIS)
Bibliographic record
Abstract
The Interdisciplinary Study of Inequalities in Smoking (ISIS) is a cohort study investigating the joint effects of residents' socio-demographic characteristics and neighbourhood attributes on the social distribution of smoking in a young adult population. Smoking is a behaviour with an increasingly steep social class gradient; smoking prevalence among young adults is no longer declining at the same rate as among the rest of the population, and there is evidence of growing place-based disparities in smoking. ISIS was established to examine these pressing concerns. The ISIS sample comprises non-institutionalized individuals aged 18-25 years, who are proficient in English and/or French and who had been living at their current address in Montréal, Canada, for at least 1 year at time of first contact. Two waves of data have been collected: baseline data were collected November 2011-September 2012 (n = 2093), and a second wave of data was collected January-June 2014 (n = 1457). Data were collected from respondents using a self-administered questionnaire, developed by the research team based on sociological theory, which includes questions concerning social, economic, cultural and biological capital, and activity space as well as smoking behaviour. Data are available upon request from [katherine.frohlich@umontreal.ca].
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".