THE BALDWIN EFFECT AND GENETIC ASSIMILATION: REVISITING TWO MECHANISMS OF EVOLUTIONARY CHANGE MEDIATED BY PHENOTYPIC PLASTICITY
Bibliographic record
Abstract
Two different, but related, evolutionary theories pertaining to phenotypic plasticity were proposed by James Mark Baldwin and Conrad Hal Waddington. Unfortunately, these theories are often confused with one another. Baldwin's notion of organic selection posits that plasticity influences whether an individual will survive in a new environment, thus dictating the course of future evolution. Heritable variations can then be selected upon to direct phenotypic evolution (i.e., "orthoplasy"). The combination of these two processes (organic selection and orthoplasy) is now commonly referred to as the "Baldwin effect." Alternately, Waddington's genetic assimilation is a process whereby an environmentally induced phenotype, or "acquired character," becomes canalized through selection acting upon the developmental system. Genetic accommodation is a modern term used to describe the process of heritable changes that occur in response to a novel induction. Genetic accommodation is a key component of the Baldwin effect, and genetic assimilation is a type of genetic accommodation. I here define both the Baldwin effect and genetic assimilation in terms of genetic accommodation, describe cases in which either should occur in nature, and propose that each could play a role in evolutionary diversification.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.005 | 0.019 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".