Bibliographic record
Abstract
Abstract If it survives for a little longer, the human race will probably start to spread across its galaxy. Germ warfare, though, or environmental collapse or many another factor might shortly drive humans to extinction. Are they likely to avoid it? Well, suppose they spread across the galaxy. Of all humans who would ever have been born, maybe only one in a hundred thousand would have lived as early as you. If, in contrast, humans soon became extinct then because of the population explosion you would have been ‘fairly ordinary’. Roughly ten per cent of all humans would have been your contemporaries. Now (as the cosmologist Brandon Carter saw to his dismay) a scientific principle tells us not to treat observations as highly extraordinary when they could easily be fairly ordinary. How to apply the principle is controversial, yet it seems we can safely conclude that humanity's chances of galactic colonization cannot be high. Still, we should work to make them as high as possible, resisting those philosophers who argue that human extinction would be no tragedy.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".