Impact of a Labour Disruption Affecting Local Public Health on the Incidence of Chlamydia Infections in Toronto
Bibliographic record
Abstract
INTRODUCTION: Labour disruptions that interrupt services can be a natural experiment to examine the effect of halting a program. A five-week municipal labour disruption in Toronto during the summer of 2009 provided an opportunity to investigate the impact of reduced sexual health services. METHODS: We examined the incidence of reported chlamydia in Toronto during the five years (2004-2008) preceding the labour disruption and during the periods just before, during, and after the labour disruption. Comparisons of actual reports for 2009 were made to immediately adjacent periods around the labour disruption, to historical trends and to forecasted rates. Interrupted time series analysis was used to test for significant differences in the trend of reported chlamydia incidence. RESULTS: There was no significant difference in the trend of reported chlamydia incidence around the time of the strike. However, there was a small but significant increase in the incidence of reported chlamydia, particularly among females under 25 years old immediately following the labour disruption. The reported incidence for this group was higher than would be expected based on annual increases and projected seasonal trends. CONCLUSIONS: There was a small increase in incidence of reported cases of chlamydia for certain groups that went beyond what is expected during the time immediately following the labour disruption. While causation cannot be implied from our ecological study, public health services may play a role in the control of sexually transmitted infections, even in the short-term. This underscores the need for future work to understand whether the changes observed can be attributed to the absence of these services.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".