The Evolutionary Developmental Biology of Tinkering: An Introduction to the Challenge
Bibliographic record
Abstract
Recent developments in evolutionary biology have conflicting implications for our understanding of the developmental bases of microevolutionary processes. On the one hand, Darwinian theory predicts that evolution occurs mostly gradually and incrementally through selection on small-scale, heritable changes in phenotype within populations. On the other hand, many discoveries in evolutionary developmental biology--quite a few based on comparisons of distantly related model organisms--suggest that relatively simple transformations of developmental pathways can lead to dramatic, rapid change in phenotype. Here I review the history of and bases for gradualist versus punctuationalist views from a developmental perspective, and propose a framework with which to reconcile them. Notably, while tinkering with developmental pathways can underlie large-scale transformations in body plan, the phenotypic effect of these changes is often modulated by the complexity of the genetic and epigenetic contexts in which they develop. Thus the phenotypic effects of mutations of potentially large effect can manifest themselves rapidly, but they are more likely to emerge more incrementally over evolutionary time via transitional forms as natural selection within populations acts on their expression. To test these hypotheses, and to better understand how developmental shifts underlie microevolutionary change, future research needs to be directed at understanding how complex developmental networks, both genetic and epigenetic, structure the phenotypic effects of particular mutations within populations of organisms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".