The Economics of Nature: Constrained Dynamic Optimization and Efficient Decentralized Decision Making in Nature
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
The paper suggests that the study of economics as being practised in the economics profession today is needlessly human centered. Evidence is presented that the driving force behind activities of all living organisms including humans is economic in nature. Their behaviors are driven by the objective of constrained dynamic optimization, i.e., that they behave rationally. Further, whenever large-scale groups are formed such as colonies of ants and bees, and trees of the forest, they resort to decentralized decision making to obtain efficiency. The evidence for this proposition is rooted in a wide range of observations on the behaviors of many plants and animals and indeed in how their genome is organized and functions. Recent research suggests that the origin of life itself had the underlying motive that was economic in nature, i.e., that life was not a chance occurrence but an inevitable outcome of energy-dissipation-driven organization of the matters behaving so as to maximize the economic efficiency along the evolutionary path of increasing entropy production. Further, observations on a wide range of natural phenomena, including straight-line path of sunlight, symmetry of snowflakes and crystals, lead us to believe that it is not just living organisms that behave rationally but inorganic matters as well rationally in the sense that they behave with the objective of constrained dynamic optimization that produces efficient outcome.
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 | 0.000 | 0.001 |
| 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