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Record W4381279234 · doi:10.1177/00207020231178394

Moving beyond the sanctuary paradigm: Canada must face up to the reality of a contested and dangerous space environment

2023· article· en· W4381279234 on OpenAlexaffabout
Patrick Perron

Bibliographic record

VenueInternational Journal Canada s Journal of Global Policy Analysis · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpace exploration and regulation
Canadian institutionsCanadian Forces College
Fundersnot available
KeywordsMilitarizationSpace policyDeterrence theorySpace (punctuation)Space debrisGlobal commonsLeverage (statistics)Government (linguistics)IdeologyCorporate governancePolitical scienceDiplomacyCommonsSociologyLaw and economicsPolitical economyLawPoliticsBusinessEngineeringComputer science

Abstract

fetched live from OpenAlex

This article outlines historical shifts in US and Canadian space policies using the sanctuary-contested policy framework. It highlights how sanctuary policies were born out of necessity rather than the pursuit of a peaceful global commons; they were never intended to, and did not, prevent the militarization and weaponization of space. The paper then describes challenges to global space governance and argues that diplomacy will not prevent conflicts in space. After introducing elements of deterrence theory, this paper concludes that Canada should move beyond the sanctuary ideology, make space a national whole-of-government issue, and align its space policy and strategy with allies and partners, credibly communicating Canada's resolve to protect and defend space assets. It further recommends that Canada develop niche capabilities that contribute to more effective national and collective deterrence and defence in space. Those capabilities should build upon existing niche strengths, not create space debris, and leverage industrial innovation in space.

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)0.006
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: Commentary · Consensus signal: none
Teacher disagreement score0.086
Threshold uncertainty score0.627

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.019
Scholarly communication0.0120.004
Open science0.0020.004
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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
GenreCommentary

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
Published2023
Admission routes2
Has abstractyes

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