Bibliographic record
Abstract
The fundamental theory of the survival of life on this planet is Darwinism. Darwinian evolution is about coping with change by changing, using what you have on hand to survive. The fuel for this process is evolutionary potential, which resides in preexisting variation. This preexisting variation allows living systems to move forward into an uncertain future. The biosphere is a complex evolutionary system that generates, stores, and uses its own potential to survive. This makes ecosystems robust, not fragile. That suggests we can use the biosphere without destroying it, but we need some guidelines. Those guidelines are embodied in the Four Laws of Biotics, which tell us how we can interact with the biosphere without endangering ourselves further. We can further improve humanity’s chances of survival as a technological species by (1) implementing the economics of well-being, (2) reducing population density by finding space in rural areas and revitalizing them into circularized economies, (3) regrowing sustainably by creating networks of cooperating circular economies, adding new modules when growth occurs, not consolidating into new densely populated and vulnerable urban centers, and (4) modifying social institutions to be responsive to the desires of the grassroots, even when those desires do not produce the expected outcomes. Darwinian principles provide humanity with a middle ground, a third way, between unattainable utopia and unacceptable apocalypse. We can alter our behavior now according to Darwinian principles, at great expense and difficulty, and extend or even improve upon the current state of the Anthropocene, or we can fail to act on our own behalf, experience a general collapse of technological society, and rebuild using those Darwinian principles to provide a more survivable future.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".