180 Occupational epidemiology: A bibliometric analysis by country and era
Bibliographic record
Abstract
<h3>Objectives</h3> Bibliographic databases allow the study of historical trends in research output <h3>Methods</h3> Countries active in occupational epidemiology were identified using the EPICOH membership list. Seven countries had more than 5 member scientists: USA, Canada, Sweden, UK, Italy, France, and Netherlands. Populations in 2000 were obtained from the UN website. Papers were sought in PubMed using “occupation*” and “epidemiolog*” in Title/Abstract. Country was obtained from the “affiliation” field. <h3>Results</h3> 7,433 papers were retrieved, the earliest from the UK in 1937 [1]. An initially steep increase in publishing has decelerated, numbers quadrupling from the 1970s to 1980s, doubling from 1980s to 1990s, but increasing by only 30% from 1990s to 2000s. The seven active countries together published 42% (3,095) of the total retrieved. No papers were retrieved from these countries before 1980, so results comparing them relate to 1980–2012. After correcting for population size, Sweden had the highest publication rate of 18.1 per million population, followed by Netherlands and Canada (7.5 and 6.7). USA, UK, France, and Italy were similar (5.2, 4.9, 4.9, and 4.6). In absolute numbers, the USA was the most prolific (1,449). <h3>Conclusions</h3> These findings must be interpreted with caution because any word search is dependent on the use of language, which varies between countries and language groups, and over time. Also, the affiliation field refers only to the first author. With these caveats, this historical analysis supports some anecdotal impressions about occupational epidemiology: Nordic countries, relative to their size, have made a major contribution; historically, papers have come from a small pool of countries; the large volume of papers from the USA is likely to be influential; and the trend of accelerating research output seen in the twentieth century may have stabilised.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".