Global and regional trends in public interest in cola and energy drinks across English-speaking countries
Bibliographic record
Abstract
A Google-linked plugin was used to investigate the trend in the public’s interest in cola and energy drinks. Seven English-speaking countries and the global context were studied for the time period between 2004 and 2022. The influence of time, the financial income situation in a given country, and the level of human development were investigated as potential independent variables concerning the population's interest in cola and energy drinks. The results of the current study indicate differences in interest in cola drinks and energy drinks among the populations of the seven English-speaking countries studied here. There are also differences between the country-specific context and the global one concerning the population’s interest in cola and energy drinks. Cola drinks are decreasing in significance as a topic of Google searches in Australia, India, South Africa, New Zealand, the United Kingdom, the United States, and Canada. A slightly different trend was observed for energy drinks, where the countries’ populations seem to search for specific brand names rather than general information related to energy drinks. The health impacts of energy drinks are of interest to the populations in the studied countries and globally. Therefore, it is likely that the public searching on Google will receive health promotion interventions related to energy drinks positively. Results from this study can form the foundation for public health approaches tackling the risk factors of non-communicable diseases in the studied countries and South Africa. Future studies should focus on a comparative analysis of public health policies and legislation in addressing the consumption of cola and energy drinks as a potential risk factor for non-communicable diseases in the studied countries and in the global context.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".