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Record W6983342394

McDonald's "U.S. Wins, You Win."

2019· article· en· W6983342394 on OpenAlexaboutno aff

Bibliographic record

VenueMurray State's Digital Commons (Murray State University) · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican Sports and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsSoviet unionPurchasingLaunchedBig businessState (computer science)European unionEvent (particle physics)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.008
GPT teacher head0.165
Teacher spread0.157 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueMurray State's Digital Commons (Murray State University)Same topicAmerican Sports and LiteratureFrench-language works237,207