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Record W316553046

International Cooperation on Environmental Issues in the Puget Sound/Georgia Basin: What Environmental Issues Could Threaten Regional Security?

2004· article· en· W316553046 on OpenAlexaboutno aff
Ann M. Lesperance, Kathleen S. Judd, Nancy Peterson

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental securityHomeland securityEnvironmental degradationNational securityEnvironmental resource managementEnvironmental planningSound (geography)Environmental studiesNatural resourcePolitical scienceResource (disambiguation)Environmental protectionBusinessGeographyTerrorismEnvironmental scienceEcologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Security is a growing concern worldwide, and homeland security has captured the attention of the United States over the past year and a half. In addition, awareness of the concept of environmental security—the notion that environmental degradation may have security implications—has been growing over the past decade. Internationally, environmental issues have direct links to security, as evidenced by the Middle East water disputes. While environmental security has not historically been a topic of major concern within the national boundaries of the United States or Canada, the environmental and development challenges that we’re facing in the Puget Sound/Georgia Basin (PS/GB), coupled with this growing concern for security, prompted a query to consider whether environmental or natural resource problems could pose a serious threat to regional cooperation or stability in the PS/GB and, hence, deserve more attention from regional decision-makers. This discussion is expected to provide a useful focus for future collaboration and integration in the PS/GB.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.553

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 studies0.0000.001
Scholarly communication0.0000.002
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 head0.246
Teacher spread0.233 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)Same topicTransboundary Water Resource ManagementFrench-language works237,207