The Ecosystem Paradigm and Environmental Risk Management
Bibliographic record
Abstract
Modern approaches to environmental evaluation and management decision making derive from ecological theories developed largely in the 1960s and earlier. Widespread use of such practices warrants a review of the status of theoretical ecology and its relationship to practical risk management decision making. Two paradigms of ecology, the Ecosystem Paradigm and Fry's Paradigm, can be summa rized in three principles: (1) in the biological levels of organization scheme there is a level of organization called “the ecosystem”; (2) to study an ecosystem, observa tions must be made at the ecosystem level of organization; (3) observations should be quantitative measurements. The literature shows that these principles have largely been ignored by ecologists when examining aquatic systems. Many theoreti cal concepts for describing the ecosystem have been proposed, but quantification is often poor or unworkable. It is evident that the “ecosystem” or “levels of organiza tion” ecological paradigm has not produced a mature theory or hypothesis of ecology as there is no generally accepted, technical, quantitative description of an ecosystem, of the other levels of organization in the scheme, or of their interrela tionships. Instead, managers, who need practical tools with reasonable predictive and explanatory power, routinely use quantitative descriptors based directly or indirectly on economics or environmental engineering in their environmental decision making.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".