Canada Dry or High Times?: A Historiographical Look at Drugs and Alcohol in Canada
Bibliographic record
Abstract
Drugs and alcohol have been featured in Canadian history as critical commodities that influenced legal decisions, social interactions, medical options, and even trade decisions. Canadian historians have examined alcohol, drugs, temperance reformers, and intoxicated Canadians in ways that deepen our understanding of how mind-altering products have influenced our Canadian values and how those ideas have changed over time. In this historiographical article, I examine how Canadian historians have responded to trends in historical scholarship that embrace a focus on social history, labour, women, medicine, colonialism, and culture. I argue that alcohol and drugs are ubiquitous in these historiographical shifts but that the uneven pace of decriminalizing intoxication has also led to new sources of information, new historical voices, and perhaps the need to rethink how our attitudes towards psychoactivity have affected our understanding of Canadian history.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".