Beyond eight forms of rarity: which species are threatened and which will be next?
Bibliographic record
Abstract
Abstract We tabulate three measures of rarity: local abundance, breeding range size and elevational extent for the passerine birds of the New World. We determine what fraction of species is threatened with extinction within the combinations of these three measures. Species with smaller ranges, lower abundances and narrower elevational bands suffer higher levels of threat across lowland, montane and island species. For a given range size, lowland species suffer higher levels of threat than island or montane species. (This is counter to the intuition that island species — and those isolated on mountain tops — might be ecologically naïve.) When all three factors are considered together, there is only a slight tendency for lowland species to be disproportionately more threatened. Simply, island and montane species tend to be relatively common within their restricted ranges and their increased abundance reduces their likelihood of being threatened. Elevation is a consistent but relatively unimportant factor in determining threat; abundance and range size are much more important, and have an interactive effect on threatened status. We calculate the number of humans with which each species shares its breeding range, and find that this number does not aid in predicting threat status.
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".