Do Us a Favour: An Exploration of Lay’s Do Us a Flavour Contest through the lens of Social Media and Brand Community Features
Bibliographic record
Abstract
This study evaluated if and how the Lay’s Do Us a Flavour campaign could be classified as a brand community and how the features of this concept in conjunction with the features of social media are reflected in the design and interactions of the site. This paper uses the theory of technological affordances and the social media features of Trust, Transparency, and Authenticity combined with the three markers of brand community as a framework to understand the user interactions and design of the site. The study found that the design of the Lay’s site was limited in its design, especially in the presence of authenticity and transparency and therefore the brand community markers of moral responsibility and consciousness of kind did not have a strong presence within the site. Based on these findings, the study determined the contest, especially when considering its temporary nature, does not demonstrate the features of brand communities and cannot be considered one in its own right but could be effective as an incentive to participate in more permanent communities.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".