Cladistic and phylogenetic biogeography: the art and the science of discovery
Bibliographic record
Abstract
Abstract All methods used in historical biogeographical analysis aim to obtain resolved area cladograms that represent historical relationships among areas in which monophyletic groups of taxa are distributed. When neither widespread nor sympatric taxa are present in the distribution of a monophyletic group, all methods obtain the same resolved area cladogram that conforms to a simple vicariance scenario. In most cases, however, the distribution of monophyletic groups of taxa is not that simple. A priori and a posteriori methods of historical biogeography differ in the way in which they deal with widespread and sympatric taxa. A posteriori methods are empirically superior to a priori methods, as they provide a more parsimonious accounting of the input data, do not eliminate or modify input data, and do not suffer from internal inconsistencies in implementation. When factual errors are corrected, the exemplar presented by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29, 427) purporting to show inconsistencies in implementation by a posteriori methods actually corroborates the opposite. The rationale for preferring a priori methods thus corresponds to ontological rather than to epistemological considerations. We herein identify two different research programmes, cladistic biogeography (associated with a priori methods) and phylogenetic biogeography (associated with a posteriori methods). The aim of cladistic biogeography is to fit all elements of all taxon–area cladograms to a single set of area relationships, maintaining historical singularity of areas. The aim of phylogenetic biogeography is to document, most parsimoniously, the geographical context of speciation events. The recent contribution by M.C. Ebach & C.J. Humphries (Journal of Biogeography, 2002, 29, 427) makes it clear that cladistic biogeography using a priori methods is an inductivist/verificationist research programme, whereas phylogenetic biogeography is hypothetico‐deductivist/falsificationist. Cladistic biogeography can become hypothetic‐deductive by using a posteriori methods of analysis.
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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 | 0.033 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.029 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".