U.S. and Canadian Governments Have Established Mechanisms to Monitor Compliance with the 2006 Softwood Lumber Agreement but Face Operational Challenges
Bibliographic record
Abstract
Correspondence issued by the Government Accountability Office with an abstract that begins "The United States and Canada have been involved in a long-standing dispute regarding the softwood lumber trade. Canada is the primary exporter of softwood lumber to the United States. In 2008, Canada exported approximately $3.2 billion worth of softwood lumber products to the United States, about 17 times the amount supplied by the next biggest exporter to the United States. After several years of litigation related to U.S. allegations of unfair Canadian subsidies, the United States and Canada signed the 2006 Softwood Lumber Agreement ("agreement"). The agreement ended ongoing litigation and requires, among other things, Canadian federal and provincial governments to establish export charges and quotas for Canadian lumber exports and for the two countries to exchange information to support monitoring compliance with the agreement. In 2008, the United States passed the Softwood Lumber Act that requires, among other things, that the U.S. government reconcile and verify softwood lumber trade data. The act also requires GAO to report on (1) whether countries that export softwood lumber or softwood lumber products to the United States are complying with international agreements entered into by those countries and the United States; and (2) the effectiveness of the U.S. government in carrying out the reconciliations and verifications mandated by the Softwood Lumber Act. This letter contains information in response to the first mandate concerning compliance with international softwood lumber agreements. In accordance with our agreement with the Senate Committee on Finance and the House Ways and Means Committee, we will issue a separate report in December 2009 that will supply additional information and findings on U.S. efforts to monitor compliance and will also address U.S. efforts to reconcile and verify softwood value data. We focused on Canada because it is the only country with which the United States has an agreement specifically related to softwood lumber and is by far the largest exporter of softwood lumber to the United States. We are not conducting a legal review of compliance with the Softwood Lumber Agreement. Our objectives in this review are to describe (1) U.S. government agency efforts to monitor compliance with the agreement, including cooperating with the Canadian government, (2) operational challenges agencies face in monitoring compliance, and (3) current compliance concerns."
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.081 | 0.028 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".