Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Explaining Culture Scientifically, edited by Melissa J. Brown, attempts to rehabilitate the concept of culture from the depravations of postmodernism by reestablishing the relevance of evolutionary science. But it does not attempt to explain postmodernism's phenomenal success in anthropology, history, and other disciplines in which the study of culture is forefront. “Evolutionary science” includes cognitivism, which, like postmodernism and the rest of “the linguistic turn,” has roots in the structuralism of Claude Lévi-Strauss. Like structuralism (which the authors barely mention) and postmodernism (which they explicitly shun), the “science” deployed in this collection comes across mainly as a brand of creationism unconnected to the legacy of Charles Darwin. Darwin's revolutionary opus inspired a number of brilliant works that pointed toward a science of culture—those of Sigmund Freud, for example—but the promise of those early years remains largely unfulfilled.
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.
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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it