Empty Stands and Empty Pockets: Revenue Generation in a Pandemic
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
The COVID-19 pandemic changed not only the way professional sports were played in 2020, but also changed the way sport-related organizations had to operate. An example of this is a fictional sports app, FanStand, that primarily offered opportunities for sports teams to engage fans through team information, in-game trivia and contests, services at games, and the purchasing of tickets and merchandise. The primary use of the app was inside arenas and stadiums, meaning that when COVID-19 stopped all play, the app was not used. Even as professional sport returned to play, fans were not attending in-person games and were not using the app. The purpose of this case study is to consider how apps like FanStand can generate revenue during the COVID-19 outbreak and beyond, using strategic and operational planning, as well as stakeholder theory, to account for various groups and individuals who are impacted by the decisions FanStand makes during this time.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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