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Record W2339974018

Ecolawgic: The Logic of Ecosystems and the Rule of Law

2015· article· en· W2339974018 on OpenAlexaff
Bruce Pardy

Bibliographic record

VenueSSRN Electronic Journal · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsCorporate governanceNatural resourcePopulationLaw and economicsBusinessGovernment (linguistics)EconomicsEnvironmental resource managementPolitical scienceLawSociology
DOInot available

Abstract

fetched live from OpenAlex

Ecosystems contain their own immutable logic: competition for scarce resources leads to natural selection, in which those organisms better adapted to conditions survive and reproduce, resulting in evolutionary change. Markets share this logic: competition for scarce resources leads to commercial success for those enterprises better adapted to economic and social conditions, producing economic variation and development. In both, the dynamics of the system arise from the interaction of a multitude of individual actions, decisions and adaptations. These basic features of ecosystems and markets are not controversial. No one versed in the ways of these systems would seriously propose to control the population of butterflies or the price of duct tape. Yet result-oriented government measures and practices have become commonplace, not because the systems are misunderstood, but because the role of the state is misconceived. Government policies are not able to dictate how ecosystems or markets work. The notion of prescribing particular ecological or economic ends conflicts with the natural behaviour of these systems and their immutable rules.Modern legal regimes do not respect how ecosystems and markets operate, but ecosystems can provide insight about how the law should work. Legal decisions should emanate from a SYSTEM of governance. Isolated, instrumentalist legal commands are incompatible with the operation of law as a system. Providing ad-hoc answers case-by-case is as much of an affront to legal principles as controlling butterflies is to the nature of an ecosystem.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.212
Teacher spread0.200 · 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 teacher head, 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

Citations2
Published2015
Admission routes1
Has abstractyes

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