Bibliographic record
Abstract
The provinces of Alberta and Ontario have chosen very different methods to distribute alcoholic beverages: Alberta privatized the Alberta Liquor Control Board (ALCB) in 1993 and established a private market to sell beverage alcohol, while Ontario, in stark contrast, opted to retain and expand the Liquor Control Board of Ontario (LCBO). This article examines the reasons for the divergent policy choices made by Ralph Klein and Mike Harris' Conservative governments in each province. The article draws on John Kingdon's “multiple streams decision-making model,” to examine the mindsets of the key decision-makers, as well as “historical institutionalism,” to organize the pertinent structural, historical and institutional variables that shaped the milieu in which decision-makers acted. Unique, province-specific political cultures, histories, institutional configurations (including the relative influence of a number of powerful actors), as well as the fact that the two liquor control boards were on opposing trajectories towards their ultimate fates, help to explain the different decisions made by each government. Endogenous preference construction in this sector, furthermore, implies that each system is able to satisfy all relevant stakeholders, including consumers.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".