Panel recovery after 22 years: how we reactivated a 45 year cohort study in Canada
Bibliographic record
Abstract
In this paper we describe the process we used to reactivate a cohort study that began in 1973 but had not been contacted since 1995. In 2018, we began efforts to trace cohort members who had been involved in the last wave of the study. While we had old contact information, we also employed internet search strategies to try to find individuals. We discuss our strategy and the limits that we have as Canadians working in an extremely limited funding landscape and a data infrastructure that does not allow access to government data sources, like those described by researchers of other similar longitudinal studies spanning decades in the UK and the US. Despite our considerable attrition, we performed some analyses that demonstrates our remaining cohort is not that dissimilar from either the original cohort or in terms of general characteristics of Ontarians in their mid-60s.
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.
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 | 0.231 | 0.265 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".