A NATIONAL EPIDEMIC WITH SEVERE LOCAL IMPLICATIONS: A Global to Local Review of Substance Use to Analyze the State of Addictions in Rural Eastern Ontario
Bibliographic record
Abstract
The dramatic rise in substance-use disorder prevalence across North America has become an urgent and escalating health issue in need of rapid intervention. In 2012, Statistics Canada conducted a study concluding that 6 million Canadians met the criteria for substance-use disorder, but even this value is thought to be an underestimate (1). It is likely this statistic has increased greatly since 2012 when considering the surging overdose crisis and significant increase in opioid-use, as well as opioid-related deaths in the past three years (2). In 2017, the cost of substance use was calculated to be $46 billion, a 5.4% increase since 2015, which factored for associated healthcare, lost productivity, criminal justice, and other direct costs (3). Substance use and addictions in Canada is therefore multifactorial, involving social, health, and economic implications.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".