McDonald's "U.S. Wins, You Win."
Bibliographic record
Abstract
McDonald's "U.S. Wins, You Win." At Los Angeles Olympics in 1984, McDonald's launched a media campaign titled "U.S. Wins, You Win." The campaign was decided after its successful success at the 1976 Montreal Olympics. The campaign consisted of gold, silver and bronze medals. How it worked was that a patron, upon purchasing an item at Mickey D's, would get a scratch-off card with an Olympic event on it. If the U.S. team won gold in that event, the patron would get a Big Mac. If the team won silver, the patron got french fries. Bronze meant a free soft drink. However, this campaign failed significantly at this time for reasons that were not considered, which led to massive losses on the company and the failure of this campaign. The difference between these two campaigns is only eight years, but much has happened that makes the second campaign not work. This paper will analyze the reasons for the failure of the second campaign despite the success of the first time and what mistakes committed by those responsible for the campaign. One of the reasons is due to the political situation between the United States and the Soviet Union. The campaign was scheduled for the 1980 Moscow Olympics, but the United States did not participate in the Olympics, so the campaign was postponed to the 1984 Los Angeles Olympics, but this year the Soviet Union also decided not to participate in the Olympics for the same reason. The withdrawal of the Soviet Union led the United States to win more medals because the Soviet Union was the strongest contender in the Olympics. That means there are more free meals that McDonald must provide, which is what made this campaign unsuccessful.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.163 | 0.046 |
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".