A network view of the transmission of sexually transmitted infections in Manitoba, Canada
Bibliographic record
Abstract
Diez Roux has used the concept of complex systems to describe approaches for the incorporation of social factors into health research. These systems consist of heterogeneous interdependent units that also exhibit emergent properties. The latter embodies the concept that the interdependent units interact with and affect each other such that the resulting properties are not simple aggregates of the individual-level properties. This paper reviews research from Manitoba with a view towards conceptualising and phrasing the observed patterns within a complex system framework. A review of the temporal and spatial patterns seen within two large sexual network databases from Manitoba was undertaken and framed against the overlying patterns of sexually transmitted infection (STI) transmission within Manitoba. The review includes a summation of STI epidemiological patterns in Manitoba over a 5-year time frame, a comparison of temporal sexual network patterns, and an analysis of network patterns in relation to disparity in STI rates. Hypotheses are generated that focus on how individual-level behaviours and interactions create the observed complex system (network) patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".