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Record W7100556735

'What's There to Lose? ' Procurement Policies and Investment Restrictions Under a Proposed Canada-EU Comprehensive Economic and Trade Agreement

2015· article· en· W7100556735 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionTreatyInvestment (military)Government (linguistics)Government procurementOrder (exchange)European communityTrade agreementFramework agreement
DOInot available

Abstract

fetched live from OpenAlex

For over half a century, Canada has engaged in liberalized trade with a block of European states. The first bilateral treaty between Canada and a formal European block dates back to 1959 when an agreement was negotiated between the Government of Canada and the European Atomic Energy Community in order to build co-operation for the peaceful use of atomic energy (EC and Government of Canada, 2008). Since then, numerous treaties have been signed between Canada and what is today the European Union (EU), while many more have been signed between Canada's national and sub-national governments and the EU's member states. Liberalized trade across the Atlantic has become an integral part of both parties' economies. In 2008, Canadian exports to the EU totalled C$36.1 billion, a 3.5 per cent increase over 2007 levels, while Canadian imports from the EU reached C$54.0 billion, increasing 9.5 per cent from 2007 (Government of Canada, 2008). The EU is one of Canada's most significant investment partners, second only to the United States (US). For 2007 alone, Canada's direct investment in the EU totalled C$122.8 billion (Government of Canada, 2008). Over the last number of years, the relative importance of

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)0.006
metaresearch head score (Gemma)0.009
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: Empirical · Consensus signal: none
Teacher disagreement score0.093
Threshold uncertainty score0.676

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0090.006
Scholarly communication0.0210.005
Open science0.0040.004
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0150.004

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 head0.278
GPT teacher head0.387
Teacher spread0.108 · 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
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
Published2015
Admission routes1
Has abstractyes

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