Did the Covid-19 Pandemic Affect the Viewer Profile for TV Dental News?
Bibliographic record
Abstract
Before the Covid-19 pandemic, educational institutions were already successfully disseminating scientific information through YouTube. This study aims to descriptively investigate viewership for the YouTube channel TV Dental News of the School of Dentistry of UFMG (Brazil) before, during, and after the Covid-19 pandemic. This is a cross-sectional study comparatively analyzing three TV Dental News viewership periods: the Covid-19 pre-pandemic period, from February 1, 2019, to February 29, 2020 (pre-Covid-19); the Covid-19 pandemic period, from March 1, 2020, to December 31, 2021 (Covid-19); and the post-peak period of the Covid-19 pandemic, from January 1, 2022, to February 28, 2023 (post-Covid-19). The results reveal a significant increase in viewers in the compared periods, particularly women and non-subscribed viewers. Viewers from abroad are becoming more common than Brazilian viewers. There has been a substantial increase in the number of views over the years analyzed, indicating that high-quality, free education that can be accessed remotely is an important source of knowledge in dentistry.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".