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Record W1998180413 · doi:10.1080/10807030091124518

The Ecosystem Paradigm and Environmental Risk Management

2000· article· en· W1998180413 on OpenAlex
Torgny J. Vigerstad, L.S. McCarty

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHuman and Ecological Risk Assessment An International Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsNexen (Canada)BIO (Canada)
FundersDalhousie University
KeywordsEcosystemEcosystem managementEnvironmental resource managementEcologyExplanatory powerSystems ecologyApplied ecologyEnvironmental scienceBiologyBiodiversityEpistemology

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.007
GPT teacher head0.259
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it