Bibliographic record
Abstract
There are a series of dualities in academia so persistent as to have the appearance of philosophical immortality: agency versus structure in sociology; nature versus nurture in psychology; good versus evil in religion and philosophy; and the public versus private in political theory.In Chapter 2, 1 borrowed Matt Ridley’s observation that “similarity is the shadow of difference: difference is the shadow of similarity” (2003: 7), to make the point that it is equally plausible to discuss “sex” similarity as it is to discuss “sex” difference; that we might argue for the relative strength of one factor or the other, but that both factors constitute sides of the same proverbial coin. In this chapter, I want to examine another duality that persists, explicitly or implicitly, throughout the literature on evolutionary theory: conformity versus diversity. Here, I refer to conformity as a conservative quality in the extent to which the morphology and behavior of living organisms are confined by law-like parameters dictated by nature. In contrast, diversity refers to the extent to which morphology and behavior express a wide range of characteristics produced through the principle of variation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".