Bibliographic record
Abstract
Throughout this book we have looked at issues framed in terms of the Linnaean hierarchy. Does membership in a species depend on the qualitative properties of its organisms or the causal relations among them? What distinguishes species taxa from such higher taxa as genera, families , and orders ? Should we adopt monism or pluralism when it comes to the species category? Thus far we have taken the Linnaean system for granted. But should we? Before addressing that question, it should be noted that the Linnaean system of classification is much more than a hierarchy of taxonomic ranks. Linnaeus also provided rules for sorting organisms into taxa, as well as rules for naming taxa. These features of the Linnaean system were premised on Linnaeus's biological theory, in particular, his assumptions of creationism and essentialism. Needless to say, these assumptions have gone by the wayside in biology and have been replaced by evolutionary theory. Still, the vast majority of biologists use the Linnaean hierarchy and its system of nomenclature. On the face of it, this may seem odd: biologists employ a system of classification whose theoretical basis has become obsolete. The continued use of the Linnaean system is more problematic when one considers that the system has lost its sorting rules, that cladistic revisions to the system render it less and less Linnaean, and that what remains of the system is flawed on pragmatic grounds.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".