The package as a weapon of influence: Changes to cigarettepackaging design as a function of regulatory changes inCanada
Bibliographic record
Abstract
INTRODUCTION: Given existing regulations that ban the tobacco industry from engaging in traditional forms of advertising and require warning labels on cigarette packaging, we suggest that one response on the part of tobacco manufacturers has been to make alterations to design elements of cigarette packages themselves. The current research seeks to examine how cigarette manufacturers have altered elements of cigarette packaging in response to regulatory changes by the Government of Canada in 2011, which increased health warning sizes on cigarette packages from 50% of the principal display surface to 75%. METHODS: Cigarette packages (n=1689) that had been on the market in Canada in the period 2001-2017 were examined and coded for package design elements including package innovation (size and package style), color (hue and saturation), and branding elements (use of iconography and variant names). Characteristics of pre-regulation packaging were then systematically compared to characteristics of post-regulation packaging. RESULTS: Many of these packaging design elements, including package size and package style, primary and secondary hue, color saturation, use of variant label names, and use of iconography have systematically varied in response to regulatory changes in Canada. For example, we observed increases in the use of flip-top (vs slide and shell) packaging, the use of yellow, black and white as the focal color, incidence of color-themed variant names, and the use of female and crest-related logos. CONCLUSIONS: The evidence suggests that many packaging design elements have varied systematically along with regulatory changes in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".