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Record W7098616267

Environment Activism or National Security Threat? Policy Options for Addressing Radical Environmental Targeting

2009· article· en· W7098616267 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMandateTerrorismNational securityContext (archaeology)Environmental securityEnergy securitySecurity policy
DOInot available

Abstract

fetched live from OpenAlex

Ecoterrorism – radical violent or destructive acts committed for environmental motives or on environmental targets – has been an under-studied domestic security concern in Canada. The seemingly intractable conflict between energy needs and environmental concerns, as exemplified by the recent series of pipeline bombings in northeastern British Columbia, has served to highlight the need for strategic thinking about this emerging threat. The question needs to be asked: who is responsible for responding to these kinds of security threats? The "'Canada First ' Defense strategy " lists terrorism response as one of the 6 core missions of the Canadian military. Does their mandate therefore extend to eco-terrorism, or are such acts better addressed as cases of civil disobedience, under the purview of the police and judiciary? We must consider the likely effectiveness of military responses for securing Canadian energy sources, particularly in the context of concerns about transnational as well as domestic eco-terrorists. This paper addresses this question and provides sets of scenarios to help guide the discussion regarding the kinds of security responses that are both necessary and feasible to address the security problem of eco-terrorism. ii

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: Other · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.0240.001

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 head0.070
GPT teacher head0.260
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 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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