MétaCan
Menu
Back to cohort
Record W3202575676 · doi:10.1177/00207020211048424

Sensing the Arctic: Situational awareness and the future of northern security

2021· article· en· W3202575676 on OpenAlexafffundabout
Benjamin T. Johnson

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaFulbright Canada
KeywordsHomeland securitySituational ethicsSituation awarenessArcticPoliticsStrategic thinkingPolitical scienceThe arcticBusinessStrategic planningTerrorismEngineeringMarketingLawEcology

Abstract

fetched live from OpenAlex

This article considers the role of surveillance within security concerns related to the Arctic in Canada and North America. More pointedly, it examines how surveillance contributes towards situational awareness and the current emphasis on technological research and development to meet current and future security requirements. The article argues that Canada's focus on surveillance within the Arctic offers a flexible strategy that navigates the complex and evolving security environment in addition to the political and fiscal realities of our time. However, the article warns that emphasizing the role of novel technology within strategic considerations risks undermining sound policymaking as the potential for new technology to transform defensive capabilities remains speculative. The article illustrates this approach to security by analyzing Canada's Arctic surveillance capabilities and goals under the All Domain Situational Awareness (ADSA) program. Further, it links Canada's efforts to North American defence by theoretically examining the role of surveillance in the Strategic Homeland Integrated Ecosystem for Layered Defence (SHIELD) concept and the recent NORAD/USNORTHCOM strategic outlook.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.312
Teacher spread0.303 · 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

Citations15
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal Canada s Journal of Global Policy AnalysisSame topicArctic and Russian Policy StudiesFrench-language works237,207