'Daily Show' quips boost Arby's sales
Bibliographic record
Abstract
Fast food chain Arby's doesn't have a beef with comedian Jon Stewart. It's losing a good sandwich salesman. Believe it or not, Stewart's quips mocking Arby's on his Comedy Central program \The Daily Show\ over the years has actually helped business. Matt Kasunic went to Arby's because he heard Stewart macking fun of it.. \He's not talking that great about arby's but he's making me hungry for Arby's\ \I am now buying arby's and getting interviewed about buying arby's because I watched that YouTube thing\ (commercial cut thank you for being a friend) Arby's spent about a half a million dollars for two commercials on one of Stewart's last shows calling him a friend for insulting their sandwiches. And on Stewart's final show, when celebrities and newsmakers taped special goodbye messages to Stewart. Arby's got the last laught.. Brown told the Wall Street Journal that the negative comments haven't hurt the Arby's brand because the social media chatter's been positive. He said sales were up over 9% for the first quarter and up 7 and a half % in the second quarter. Arby's made a tounge in cheek offer to hire Stewart when he announced he was leaving the Daily Show. Stewart, said no thanks. I'm Ron Brown. You're listening to Rivet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.198 |
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; both teacher heads agree on what is shown here.
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".