David Kirby on Mercury in Vaccines & the Secret US Vaccine Court
Bibliographic record
Abstract
Journalist David Kirby explores the chilling possibility that a vaccine additive may be fueling an apparent epidemic of autism, ADD, speech delay and other disorders in America’s children. In the 1990’s, reported autism cases among American children began spiking, from about 1 in 10,000 in 1987 to a shocking 1 in 166 today. In this period, new shots containing a mercury-based preservative called Thimerosal were added to the nation’s already crowded vaccination schedule. At the same time, some parents noticed that their healthy children were descending into silent, disturbed, and physically ill behavior after receiving vaccinations. In 1999, the FDA announced that children were being exposed to mercury at very young ages at levels far exceeding federal regulations, but the public health establishment failed to take parental concerns about the impact seriously. David Kirby joined Joe Broadhurst of CKUT Radio in Montreal to discuss the relationship of Autism and mercury in vaccines.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.172 | 0.004 |
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; both teacher heads agree on what is shown here.
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".