Are you ready for it? Harnessing celebrity influence for science communication and seismology – The Taylor Swift effect
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
In June 2024, Taylor Swift performed three sold-out nights at Dublin's Aviva Stadium. We pioneered a unique method of scientific engagement by designing a seismological campaign alongside her performances. We installed 42 temporary seismometers in 21 different locations around the concert venue so that we could record and compare the seismic impact of the concert with the national seismic network recordings. Our social and traditional media campaigns sparked significant public interest. Post-concert, we analysed seismic data and shared the findings with public audiences, inviting fans to contribute concert videos for seismic analysis. By examining social and traditional media output via methods such as Latent Dirichlet Allocation we have highlighted pop culture's potential to engage citizens and foster scientific understanding of cultural 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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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