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Record W2093388913 · doi:10.3152/147154606781765066

Environmental assessment of Canadian trade and investment negotiations

2006· article· en· W2093388913 on OpenAlexaffabout
Rachel McCormick, Jaye Shuttleworth, Shenjie Chen

Bibliographic record

VenueImpact Assessment and Project Appraisal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsNegotiationInvestment (military)International tradeGovernment (linguistics)BusinessPerspective (graphical)Promotion (chess)Trade promotionTrade barrierForeign direct investmentEconomicsFree tradePolitical scienceComputer science

Abstract

fetched live from OpenAlex

The 2001 Framework for Conducting Environmental Assessments of Trade Negotiations is being applied to multilateral, regional and bilateral trade negotiations and foreign investment promotion and protection agreements. This article provides an overview of the challenges and lessons learned during these assessments from the perspective of the environmental assessment of the Trade Secretariat for the Government of Canada. Recent efforts have focused on application of the Framework to investment negotiations, improving consultations and communications, and addressing the ongoing challenge of data limitations. The article closes with a discussion of some issues that require continued consideration by environmental experts and trade negotiators working in impact assessment of trade and investment negotiations.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.810

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.010
Science and technology studies0.0060.001
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.016
GPT teacher head0.338
Teacher spread0.322 · 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 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

Citations1
Published2006
Admission routes2
Has abstractyes

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