Bibliographic record
Abstract
For decades, biogeographers have sought a better understanding of how organisms are distributed among islands. However, the island biogeography of humans remains largely unknown. Here, we investigate how human population size varies among 486 islands at two spatial scales. At a global scale, we tested whether population size increases with island area and declines with island elevation and nearest mainland, as is common in non-human species, or whether humans escape such biogeographic constraints. At a regional scale, we tested whether population sizes vary among islands within archipelagos according to the positioning of different cultural source pools. Results illustrate that on a global scale, human populations increased in size with island area, similar to non-human species, yet they did not decline in size with elevation and distance to nearest mainland. At a regional scale, human population size often varied among islands within archipelagos relative to the location of different cultural source pools. Despite broad-scale similarities in the geographical distribution of human and non-human species among islands, results from this study indicate that the island biogeography of humans may also be influenced by archipelago-specific social, political and historical circumstances.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".