Beyond Set Theory: The Relationship between Logic and Taxonomy from the Early 1930 to 1960
Bibliographic record
Abstract
In this dissertation I look at the relationship between logic and taxonomy as taxonomists responded to double attack: an attack on their methodology from the biological community during the 1930s and at the start of a methodological civil war that erupted in late 1950s. According to the usual story, the relationship between logic and taxonomy could not have been worse. Taxonomists were thought to be either mired in Aristotelian essences or lost in some dubious set-theoretic wasteland. This story, however, is now recognized as being a political tool rather than an accurate history and the time is ripe for something new. I examine four cases: British botanist John Gilmour, American paleontologist George Gaylord Simpson, German entomologist Willi Hennig, and American philosopher Morton Beckner that help illustrate the richness of this relationship. These cases will show how different branches of logic successfully played roles in taxonomy’s methodological reform, rather than set-theory playing the dominant and ultimately failing role as the old paradigm. In addition, it will become clear that one reason why this could be done was because many of these taxonomists were part of transient interdisciplinary groups willing to relax the standards of authority within interdisciplinary communities. These changes in authority helped facilitate communication and promote knowledge production during this complex time. Taxonomists without the traditionally recognized expertise in logic chose to read logic on the fly, and likewise philosophers and other biologists without established training in taxonomy could enter the debate in significant and productive ways.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".