Nothing in Popular Culture Makes Sense except in the Light of Evolution
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
An evolutionary lens can inform the study of cultural forms in a myriad of ways. These can be construed as adaptations, as exaptations (evolutionary byproducts), as gene–culture interactions, as memes, or as fossils of the human mind. Products of popular culture (e.g., song lyrics, movie themes, romance novels) are to evolutionary cultural theorists what fossils and skeletal remains represent to paleontologists. Although human minds do not fossilize or skeletonize (the cranium does), the cultural products created by human minds do. By identifying universally recurring themes for a given cultural form (song lyrics and collective wisdoms in the current article), spanning a wide range of cultures and time periods, one is able to test key tenets of evolutionary psychology. In addition to using evolutionary psychology to understand the contents of popular culture, the discipline can itself be studied as a contributor to popular culture. Beginning with the sociobiology debates in the 1970s, evolutionary informed analyses of human behavior have engendered great fascination and animus among the public at large. Following a brief summary of studies that have explored the diffusion of the evolutionary behavioral sciences within specific communities (e.g., the British media), I offer a case analysis of the penetration of evolutionary psychology within the blogosphere, specifically the blog community hosted by Psychology Today.
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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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