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Sustainable Development: Lessons from the Paradox of Enrichment

2001· article· en· W2004305729 on OpenAlexaff
Jae S. Choi, Bernard C. Pattent

Bibliographic record

VenueEcosystem Health · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsSustainabilityBalance (ability)ExploitSimple (philosophy)Set (abstract data type)Relevance (law)Action (physics)Order (exchange)PopulationSustainable developmentEconomicsPositive economicsEcologyComputer scienceEpistemologySociologyBiologyPolitical sciencePhysicsLaw

Abstract

fetched live from OpenAlex

Abstract With the current struggle to “sustainably” exploit our biosphere, the “paradox of enrichment” remains an issue that is just as relevant today as it was when it was first formalized by Rosenzweig in 1971. This paradox is relevant because it predicts that attempts to sustain a population by making its food supply more abundant (e.g., by nutrient enrichment) may actually have the reverse (paradoxical) effect of destabilizing the network. Originally, this paradox was based upon studies of “reasonable,” but quite simple, predator‐prey models. Here, we attempt a more “realistic” revision of the paradox that explicitly accounts for the embedded nature of the human system in a complexly interwoven set of hierarchical (spatial, temporal, and organizational) relations with the rest of the ecosphere‐a relationship whose exploitative nature continues to grow in intensity and extent. This revision is attempted with the aid of a combined thermodynamic and network approach. The result is that a scaledependent asymmetry in the action of the second law of thermodynamics is shown‐an asymmetry that results in the creation of two antagonistic propensities: local order and local disorder. The point of balance between these two propensities is empirically measurable and represents a balance between processes and constraints internal (growth and development) and external (interactive and perturbing influences) to a system‐a balance that may be called the most “adaptive” state (after Conrad 1983). The use of such an index of this balance is demonstrated and it is used to clarify the relevance of the paradox to more complexly organized systems. As a consequence, we conclude that the concept of “sustainable exploitation and growth” is an oxymoron.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.012
Scholarly communication0.0030.007
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2001
Admission routes1
Has abstractyes

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