Challenges and Opportunities for Using Administrative Data to Explore Changes in Health Status: A Study of the Closure of the Newfoundland Cod Fishery
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 closure of the cod fishery in Newfoundland and Labrador has had dramatic social and economic impacts on fishing communities in the province. Following a limited closure in 1992, a more extensive closure followed in 1994, which is still in force today, although income support provided to displaced fishery workers ended in 1999. A population-based study was conducted in 2004/2005 using 7 different sources of administrative and survey data to investigate a range of social, demographic, and health changes in fishing communities affected by the closure of the cod fishery from the period 1991 to 2001. Findings of this study extend our understanding of the impact of the fishing moratorium in Newfoundland. This article also presents both the challenges to and opportunities for using administrative and survey data to explore the impact of the fishery closure on the health and well-being of Newfoundland fishing communities. One of the most significant challenges to using administrative and survey databases was the inconsistencies in how communities were identified across the various databases. Although not without limitations, administrative data is a cost-effective means to explore the impact of socioeconomic change on a population's health status.
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 | 0.002 | 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 | 0.001 | 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