Crisis Text Line Benefit Festival: An Applied Study in Event Planning and Practice
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
For my Honors Capstone Project, I created and hosted my own benefit concert as an opportunity to gain real experience in event management, booking, production, marketing, and promotion. Although I’d had incredible experiences in my extracurricular activities and internships, I had not yet been able to conceptualize my own event and see it all the way through. The Crisis Text Line Benefit Festival took place on Wednesday, October 25, 2017, at Funk N’ Waffles in downtown Syracuse. All proceeds were donated to Crisis Text Line, a non-profit organization that provides 24/7 counseling services via text message. The two performers were Laura Stevenson, an indie rock singer from Rosedale, NY and Cat Clyde, a blues singer from Stratford, Ontario. In addition to the live performances, the show was live streamed online for donations, provided custom merchandise, and had two component pages for ancillary fundraising. Money raised from this event helped to save more lives each day by funding counselor training, covering texting fees for thousands of at-risk texters, or expediting the global expansion of Crisis Text Line. My goals for my Honors Capstone Project were to hone these event planning and promoting skills and become a better music industry professional while doing my part for suicide prevention.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.001 | 0.001 |
| 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