Darwin's Finches or Lamarck's Giraffe, Does International Relations Get Evolution Wrong?
Bibliographic record
Abstract
Following the recent 150th anniversary of the publication of The Origin of Species, we are in the midst of a surge of Darwinian models of social change in international relations and even genetic and sociobiological analyses of politics more generally. But does being correct biologically make the Darwin/Mendel synthesis an appropriate model of change in world politics? This is an open question and one made interesting by the existence of multiple discarded models of biological evolution, most prominent among them being Lamarck's model of inheritance of acquired characteristics. So we can also ask, conversely, does being incorrect biologically disqualify a model for use in international relations? In this article, we explore this question by examining the challenges of evolutionary analysis and analyzing Lamarckian evolution side by side with Darwinian evolution. If IR is to pursue evolutionary analysis, we argue that Lamarck deserves a second look.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".