Business Against Drunk Driving: The Neoliberal State, Labatt Brewery, and the Creation of the “Responsible Drinker”
Bibliographic record
Abstract
This paper examines the motivations and consequences of Labatt’s anti–drinking and driving campaign. The paper considers the economic and political conditions that enabled Canada’s largest brewer to execute a cause-advertising campaign and to establish itself as a “responsible corporation”—even when its leadership cared less about the deleterious effects of Labatt products and more about the company’s earnings. It examines neoliberal governance and the relationship between the public and private sector in tackling a prominent social problem—impaired driving—and how a for-profit business used its influence to create a new subjectivity: the “responsible drinker,” who did not drive while under the influence. It seeks to situate Labatt’s campaign within an increasingly neoliberal, individualistic political economy. This paper argues that Labatt’s actions were part of the neoliberal agenda toward “responsibilization” that shifted the responsibility for drunk driving away from regime-based institutions and onto the individual, allowing the neoliberal state to govern from a distance. It demonstrates that contrary to neoliberal rhetoric the state did not shrink during the late twentieth century but rather took on new regulatory functions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.029 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| 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".