Bibliographic record
Abstract
Ecosystems contain their own immutable logic: competition for scarce resources leads to natural selection, in which those organisms better adapted to conditions survive and reproduce, resulting in evolutionary change. Markets share this logic: competition for scarce resources leads to commercial success for those enterprises better adapted to economic and social conditions, producing economic variation and development. In both, the dynamics of the system arise from the interaction of a multitude of individual actions, decisions and adaptations. These basic features of ecosystems and markets are not controversial. No one versed in the ways of these systems would seriously propose to control the population of butterflies or the price of duct tape. Yet result-oriented government measures and practices have become commonplace, not because the systems are misunderstood, but because the role of the state is misconceived. Government policies are not able to dictate how ecosystems or markets work. The notion of prescribing particular ecological or economic ends conflicts with the natural behaviour of these systems and their immutable rules.Modern legal regimes do not respect how ecosystems and markets operate, but ecosystems can provide insight about how the law should work. Legal decisions should emanate from a SYSTEM of governance. Isolated, instrumentalist legal commands are incompatible with the operation of law as a system. Providing ad-hoc answers case-by-case is as much of an affront to legal principles as controlling butterflies is to the nature of an ecosystem.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".