An Analysis of the Relationship between Sociodemographic Features and Complaints of Bed Bug Infestations at the Population Ward Level in Toronto.
Bibliographic record
Abstract
such as distant and intermediate sociodemographic factors, responsible for the resurgence of this prehistoric pest. In this retrospective descriptive study with ecological association, Social Determinants of Health approach and Descriptive Correlation Research framework were used for predicting and explaining those possible relationships between the selected sociodemographic features (independent variables), and the number of bed bug complaints in 2009 and 2010 by ward-level (dependent variables) in Toronto. Independent variables like apartment buildings with <5 storeys (Spearman’s rho=0.555,p=0.006/rho=0.571,p=0.002), rental dwellings (rho=0.590,p<0.001/ rho=0.623,p<0.001), multi-family households (rho=-0.405,p=0.002/rho=-0.421,p=0.002), and work (Pearson correlation: r=0.538,p<0.001/r=0.600,p<0.001) and non-work (r=0.652,p<0.001/r=0.648,p<0.001) trips by transit appeared to have a relationship with the number of complaints received in 2009 and 2010. The aforesaid independent variables were responsible for 16-43% of variation in the number of complaints. This study was able to demonstrate a statistical correlation between some of these sociodemographic features, and bed bug infestations reflected in the complaints received by Toronto Public Health. The results of this particular study are considered to be helpful in increasing community partnerships and leadership from Toronto Public Health in dealing with various bed bug-related issues.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".