Bibliographic record
Abstract
Even after all this time, whenever I see that hair-on television, in the pages of a magazine, glowing on my computer screen-my first impulse is to laugh.The coif is so contrived, so Halloweenish, he looks like a peach-coloured Elvis.But I don't laugh; instead, I feel queasy.I even feel a touch of guilt, as if I had been about to laugh at someone whose head is deformed.Repellent hair-what ill-fated circumstances (there must have been many) led him to violate it?Not that he wants sympathy, much less understanding.He wants magic.He wants to turn back time.His hair is at war with time, with being the age he is.Pop wisdom has it that you are only as old as you think you are.You can age backwards!Buy time!But buyer beware: to the extent that anyone can deny something as intimate, natural, and elemental as aging, he can deny anything.*** He will unleash a racist kleptocracy.It will be autocratic and infantile in depressingly familiar ways, but I do not think fascist, except in the loose sense of the word to mean repressive.He is not America's Mussolini.The world survived Mussolini.It has survived worse, much worsewhich is no consolation.Trump is the public face of forces far more dangerous than fascism.The world we know cannot survive extreme global warming.This, along with mass extinction and nuclear war, subsume all other dangers.*** Physics, as Bill McKibben says, doesn't care.It doesn't care about justice or catastrophes or hair that looks like a duck.Physics doesn't care about the human species.We do not have a Ten Commandments for a time of nuclear weapons, or a Sun Tzu to tell us how to fight mass extinction.We know only that we need something we do not have: a functional ecological culture based on reciprocity and sustainability, whatever those words may mean.We need the alertness of hunter-gatherers.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.121 | 0.031 |
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 source (direct Gemma or distilled Codex), 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".