Bibliographic record
Abstract
Turn now to those who think natural selection is vastly overrated as a cause of evolutionary change. It is at best a clean-up process after the real creative work has been done. It is little surprise that these critics come from within the organismic model, implicitly or explicitly. At the scientific level, we have encountered already the most (and properly) distinguished of them all, the American population geneticist Sewall Wright. Remember his “shifting balance theory,” where the key lay in genetic drift, as gene levels fluctuated randomly in small subpopulations, and then, when new adaptive features appeared, the subpopulations rejoined the larger group (probably the species), and through a form of group selection the new feature spread through the whole group. This is highly Spencerian – infused with a solid dose of Bergsonian vitalism – as equilibrium is disturbed and then regained at a higher level, part of an overall progressive process, presumably ending in humankind.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.010 | 0.024 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.047 | 0.013 |
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".