Emergence, nonlinearity, and living systems: A metaphysical lecture from biology?
Bibliographic record
Abstract
It is widely believed among philosophers that a higher-level property, if it is a physical property, must be instantiated by a complex structure consisting of more basic physical properties. Dynamic properties of a higher than the most basic level are thus merely recombination of atomic properties. Consequently, no dynamics describing changes in the world, such as development, and/or interactions between physical, chemical, biological, or other systems, can possibly contradict this claim. Traditionally analogically emergent properties are understood to be novel "internal" properties of complex entities that cannot be reduced to lower-level properties. Taxonomies of emergence driven by reductionist motives regard such properties as mythical (e.g. vital force), acknowledging a possibility of only epistemic emergence in the world of physical properties. I propose in response that such a taxonomy may be incomplete. Biological systems as they are explained in terms of non-linear dynamics, I suggest, may fit requirements of non-epistemic emergence, exhibiting properties of relationally holistic systems. In a system explained in terms of nonlinear dynamics, none of the external properties influencing the system is singled out as the cause of its abrupt changes. Instead, a relation among the constituents of the system seems to be responsible for such a turn of events. I illustrate applications of nonlinear dynamics to the cases of metabolic control and biological pattern-formation. I outline relevant conceptual and empirical questions that should be addressed in order to answer whether the accounts concerning biological and possibly other types of natural systems which appeal to nonlinear dynamics, may be suggesting that behavior of these systems goes beyond epistemic emergence.
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 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 | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".