Mega-Special-Event Promotions and Intent to Purchase: A Longitudinal Analysis of the Super Bowl
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mega-special-event properties (sponsees) have the ability to attain significant resources through sponsorship by offering exclusive promotional opportunities that target sizeable consumer markets and attract sponsors. The Super Bowl, one of the most watched television programs in the world, was selected as the mega-special-event for this study as it provides a rare environment where a portion of the television audience tunes in specifically for the purpose of watching new and entertaining commercials. A longitudinal analysis of consumer opinion related to the 1998, 2000, 2002, 2004, and 2006 Super Bowls provides empirical evidence that questions the ability of Super Bowl sponsorship to influence the sales of sponsor offerings. Results pertaining to consumers’ intent to purchase sponsors’ products—one of the most sought after metrics in relating sponsorship effectiveness to sales—demonstrate that levels of intent-to-purchase inspired by sponsorship of the Super Bowl is relatively low and, most importantly, that increases are not being achieved over time. These findings have implications for both mega-sponsees and their sponsors as well as media enterprise diffusing mega-special-events.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it