MétaCan
Menu
Back to cohort
Record W1999919508 · doi:10.1177/0883073811432294

Public Perception of Tourette Syndrome on YouTube

2012· article· en· W1999919508 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Child Neurology · 2012
Typearticle
Languageen
FieldPsychology
TopicObsessive-Compulsive Spectrum Disorders
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsTourette syndromePsychologyPerceptionNeuroscienceMedicinePsychiatry

Abstract

fetched live from OpenAlex

We sought to determine public perception surrounding Tourette syndrome through viewers' responses to videos on YouTube. The top 20 videos on YouTube for search terms Tourette's, Tourette's syndrome, Tourette syndrome and tics were selected. The portrayal of Tourette syndrome was assessed as positive, negative, or neutral. Top 10 comments for each video were graded as "sympathetic," "neutral," or "derogatory." A total of 14 970 hits were obtained and 41 videos were retained, with an average of 590 113 views (1369 to 13 747 069) and 1761 comments (0 to 35 241). Twenty-two percent of videos retained portrayed Tourette syndrome negatively, 20% were neutral and 59% positive. Negative portrayals were significantly associated with more views (Spearman correlation rho = -.46, P =.003) and comments (Spearman correlation rho = -.47, P = .002). Although excellent examples of Tourette syndrome are available on YouTube, the popularity of negative portrayals may reinforce existing stigma in society.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.021
GPT teacher head0.276
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it