Advertising Restrictions and Competition in the Children's Breakfast Cereal Industry / Restrictions et compétition publicitaire dans l'industrie des céréales pour enfants
Bibliographic record
Abstract
This paper takes advantage of the ban on advertising directed at children in the province of Quebec to study the effect of advertising in the children's breakfast cereal industry. Advertising is viewed alternatively as anti-competitive, if it increases brand loyalty, or as pro-competitive, if it acts a substitute for brand recognition. I construct a model of established and non-established brands in which advertising serves to inform consumers about the existence of brands. The model predicts that the effect of prohibiting advertising is to permit established brands to enjoy greater market share at the expense of newer and less well-known brands. This prediction is supported by the data: older, better-known brands have higher market share in Quebec than in regions where advertising is permitted and the opposite is true for non-established brands. This result suggests that in this market the effect of advertising cannot be to increase perceived product differentiation and reduce competition. Nous prenons avantage de l'interdiction de diffuser de la publicite a l'intention des enfants au Quebec pour etudier l'effet de la publicite dans l'industrie des cereales. La publicite est consideree comme etant anti-concurrentielle si elle augmente la loyaute envers la marque, alors qu'elle est vue comme etant benefique pour la concurrence si elle agit comme un substitut a la reconnaissance de la marque. Nous construisons un modele de marques etablies et non-etablies sur le marche ou la publicite a pour but d'informer les consommateurs sur l'existence des marques. Le modele predit que toute prohibition de la publicite a pour consequence de permettre aux marques etablies d'augmenter leur part de marche au detriment de celles qui sont nouvelles et moins connues. Ce resultat est valide par les donnees. En effet, les marques les plus anciennes et les mieux connues ont des parts de marche plus elevees au Quebec que dans les regions ou la publicite est permise. L'inverse est vrai pour les marques non-etablies. Notre resultat suggere que dans ce marche, la publicite ne peut pas augmenter la differenciation de produit et reduire la concurrence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".