Bibliographic record
Abstract
Abstract Geologists have declared an epochal transition to the Anthropocene, formally recognizing humans as the driving force of destructive global change; a distinction can no longer be made between human history and natural history. Certain commentators argue that Capitalocene better characterizes the situation, given that the effects of planetary decimation and global warming are not equally distributed among humans. A second conceptual change has recently taken place in which genomes are recognized as reactive to environmental stimuli both external and internal to the human body. In the post‐genomic era, genes neither initiate life nor drive human development. The science of the bourgeoning field of behavioural epigenetics is introduced, followed by illustrative examples of environmentally caused epigenetic changes that impact negatively on health. Epigeneticists routinely delimit their attention to detecting measurable changes at the molecular level. It is argued that anthropological contributions that incorporate subjective accounts of embodiment involving past and present events are crucial in order to better situate and account for biological differences and health outcomes historically, ecologically, and politically. Discussion of the microbiome provides a cautionary reminder that microbes are the ultimate driving force of health and illness. In conclusion, the Earth Optimism movement is briefly introduced, as is the concept of resilience, but alone these positive moves will not curb unremitting global warming.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.031 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".