From the sidelines to the headlines: How youth leveraged online technologies during the pandemic to drive a national policy advocacy campaign against predatory diet pills — A case study
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
Soon after the onset of the COVID-19 pandemic in 2020, much of the analog world as we knew it ground to a halt, jettisoning most arenas of life into the digital sphere. Among those who quickly gained facility with online ways of interacting and conducting business included youth and U.S. state lawmakers — two communities that rarely interacted prior to the pandemic. Within months, key means of civic participation had shifted online, leading to the genesis of the Youth Corps, a virtual youth policy advocacy program of the Strategic Training Initiative for the Prevention of Eating Disorders (STRIPED). In this case study, we introduce the theoretical frameworks that provide the basis for the digital STRIPED Youth Corps, describe the growth and successes of the program through the early years of the pandemic, and discuss lessons learned and future directions for continued virtual youth policy advocacy.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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