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Record W2489230631 · doi:10.1016/s1064-4857(04)10013-2

THE CANADA-U.S. SOFTWOOD LUMBER DISPUTES

2004· book-chapter· en· W2489230631 on OpenAlexfundaboutno aff
Harry W. Nelson, Ilan Vertinsky

Bibliographic record

VenueResearch in global strategic management · 2004
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
FundersALS Society of CanadaU.S. Department of Commerce
KeywordsNormativeDispute resolutionSoftwoodEconomicsBusinessPolitical scienceInternational tradeEngineeringLawPulp and paper industry

Abstract

fetched live from OpenAlex

Disputes about Canadian exports of softwood lumber to the U.S. have persisted for more than a century. In this paper the roots of the disputes and the prospects for their resolution are examined. The focus is on the following key factors: (1) the nature of supply and demand; (2) the normative differences underlying the systems of timber management in the two countries and differences about what constitutes a “level playing field”; (3) rent seeking by stakeholders; and (4) weakness in bilateral and multilateral trade dispute resolution institutions. The paper concludes that there are good reasons to expect short term solution to the current dispute but persistence of the disputes in the long run.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.073
Threshold uncertainty score0.529

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0100.005
Scholarly communication0.0060.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.045
GPT teacher head0.306
Teacher spread0.261 · 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
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

Citations2
Published2004
Admission routes2
Has abstractyes

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