Geriatric Politics and the American Presidential Election
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
When Anita Wohlmann and Aagje Swinnen invited me to write a commentary on age and ageism in the upcoming 2024 American presidential election, I was entranced by the idea. As a Canadian, I have watched with fascination the dramas of American elections from the front row of our international border, beginning with the 1960 debates between Democrat John F. Kennedy and Republican Richard M. Nixon, the first on TV. Both were experienced politicians. Kennedy was a senator and Nixon had been Vice President under Dwight Eisenhower for eight years, thus expected to be debate winner and next President. But TV was not kind to him. Kennedy appeared fit, handsome, charismatic, camera friendly, and most importantly, much younger than Nixon, who was awkward, uncomfortable, hesitant, and sweaty (also recovering from a knee injury). Both were in their forties, Nixon only five years older than Kennedy (see Kraus, 1977).
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 | 0.000 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 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 it