The scope of Baker's law
Bibliographic record
Abstract
Summary Baker's law refers to the tendency for species that establish on islands by long‐distance dispersal to show an increased capacity for self‐fertilization because of the advantage of self‐compatibility when colonizing new habitat. Despite its intuitive appeal and broad empirical support, it has received substantial criticism over the years since it was proclaimed in the 1950s, not least because it seemed to be contradicted by the high frequency of dioecy on islands. Recent theoretical work has again questioned the generality and scope of Baker's law. Here, we attempt to discern where the idea is useful to apply and where it is not. We conclude that several of the perceived problems with Baker's law fall away when a narrower perspective is adopted on how it should be circumscribed. We emphasize that Baker's law should be read in terms of an enrichment of a capacity for uniparental reproduction in colonizing situations, rather than of high selfing rates. We suggest that Baker's law might be tested in four different contexts, which set the breadth of its scope: the colonization of oceanic islands, metapopulation dynamics with recurrent colonization, range expansions with recurrent colonization, and colonization through species invasions. Contents Summary 656 I. Introduction 657 II. What is Baker's law, and how did it originate? 658 III. Mate limitation during mainland–island colonization 660 IV. Mate limitation in metapopulations 661 V. Mate limitation during species introductions and invasions 663 VI. Mate limitation during range expansions and evolution at range margins 663 VII. Pollinator limitation, the evolution of dispersal, and the scope of Baker's law 664 VIII. Conclusions and future perspectives 664 Acknowledgements 665 References 665
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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".