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Record W2904109947 · doi:10.1007/978-94-6265-267-5_16

Why Was Canada Not in the Room for the Nuclear Ban Treaty?

2018· book-chapter· en· W2904109947 on OpenAlexfundaboutno aff
Marilou McPhedran, David D. Hebb

Bibliographic record

VenueT.M.C. Asser Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNuclear Issues and Defense
Canadian institutionsnot available
FundersUniversity of Manitoba
KeywordsDisarmamentTreatyArms controlNuclear weaponPolitical scienceLawParliamentMandateNuclear ethicsNegotiationPublic administrationPolitics

Abstract

fetched live from OpenAlex

This chapter examines Canada’s lost opportunities for leadership in arms control and nuclear non-proliferation. Canada’s decades-long record for promoting non-proliferation norms ranges from active support for the Nuclear Non-Proliferation Treaty that became international law in 1970 to former Prime Minister Pierre Trudeau’s peace initiative in 1983, through to Canada’s influential push leading to the NATO nuclear policyNATO Nuclear policy review in 2000 and the 2005 all-party resolution in Canadian Parliament on prohibition of nuclear weapons. Why Canada chose not to champion the 2017 UN Treaty on the Prohibition of Nuclear Weapons, instead voting against the UN General Assembly resolution in 2016 that established the mandate for nations to negotiate the treaty and falling in line with the US-led NATO boycott of negotiations, is examined. The authors conclude that Canadian civil society leadership continues to be essential to a return by the Canadian Government to independent thinking and leadership on nuclear disarmament.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.104
Threshold uncertainty score0.751

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0150.007
Scholarly communication0.0080.003
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0160.003

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 head0.052
GPT teacher head0.282
Teacher spread0.230 · 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 designNot applicable
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

Citations2
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueT.M.C. Asser Press eBooksSame topicNuclear Issues and DefenseFrench-language works237,207