Exploring Attitudes of Pakistani and Canadian Children towards Television Advertisements: A Cross-cultural Comparative Analysis
Bibliographic record
Abstract
Children from different socio-cultural backgrounds experience and cognise television advertisements differently, which is always interesting research area to investigate. Previously advertising researchers have reported that children are valuable consumers with the ability to develop their own attitudes towards television advertisements. This article reports findings from a qualitative study that examines children’s attitudes towards television advertisements in a cross-cultural context. Focus-groups were conducted in Pakistan and Canada because of distinctive cultural differences between the two countries. In all, 72 children volunteered to partake the study (N = 72) where 36 participants were recruited from Canada and the same number of Pakistani teens participated. The study compared the attitudes of Canadian and Pakistani teenagers towards television advertisements in the product category of foods and snacks. This research study is unique in presenting a cross-cultural picture of children’s attitudes towards televised food advertisements. The uniqueness of study is evident in its contribution to the cross-cultural consumer socialisation phenomenon that would be beneficial for practitioners and regulatory authorities. The findings outline significant differences between the two subject groups. Importantly, the study presents theoretical and practical implications for researchers. It adds to the literature related to children’s socialisation issues and attitudes towards television advertisements. Additionally, it highlights key implications for marketing agencies that strive to develop a foothold in Pakistani and Canadian food markets.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".