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Record W2129289415 · doi:10.22230/jem.2004v4n1a256

Evolving ecosystem management in the context of British Columbia resource planning

2004· article· en· W2129289415 on OpenAlexaffabout
Warren Mabee, Evan Fraser, Olav Slaymaker

Bibliographic record

VenueJournal of Ecosystems and Management · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsUniversity of British Columbia
FundersDepartment of Foreign Affairs and Trade, Australian Government
KeywordsEcosystem managementNatural resource managementEnvironmental resource managementEcosystemResource management (computing)Natural resourceEcosystem servicesEcosystem-based managementLivelihoodContext (archaeology)BusinessEcosystem healthTotal human ecosystemEnvironmental planningComputer scienceEcologyGeographyEnvironmental scienceAgriculture

Abstract

fetched live from OpenAlex

Ecosystem management is an approach to natural resource planning that theoretically places environmental issues on an equal footing with the economic concerns that dominate resource use. This approach recognizes the importance of both a healthy environment and access to natural resources. Each of these factors is an implicit element of human security, a political concept that promotes the protection of human lives and livelihoods. Ecosystem management acknowledges the role of humans as an integral part of the ecosystem; however, it does not define the ways in which humans and the ecosystem interact. This lack of definition makes the practical application of ecosystem management difficult.In this paper, we examine the application of ecosystem management principles in British Columbia's Clayoquot Sound. We propose that human security can act as an imperative for the expanded consideration of social networks and environmental pathways in the practice of ecosystem management. Theories from the social and natural sciences are supplied to support the science-based application of ecosystem management. These underpinnings enable managers to better define ecosystem boundaries and to integrate expanded social networks into management plans.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
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 studies0.0000.000
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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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 designObservational
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

Citations7
Published2004
Admission routes2
Has abstractyes

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