Projections of Washington-British Columbia Trade and Traffic by Commodity, Route and Border Crossings
Why this work is in the frame
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Bibliographic record
Abstract
Continuing adaptation to the changing transportation needs of the U.S. and Canada is critical in maintaining efficiency and reducing costs of raw and manufactured goods. As NAFTA moves into its twelfth year of existence, there is a growing need to continue adapting to the changing transportation environment. With bilateral trade in excess of $1.2 billion per day between the U.S. and Canada and over 200 million annual crossings (passenger vehicles and freight trucks), knowledge of the composition of commodities crossing the border allow for easier adjustment to and support for the changing needs of industries and transportation providers. Since Washington borders Canada and acts as an international trade hub for the state as well as industries throughout the United States, there is a specific need to evaluate the composition of commodities at its key border ports in order to project future traffic. This project identifies key commodity groups in order to create a profile of major and minor Washington border ports in order to develop traffic projections. The central resource used to create the profile is the Strategic Freight Transportation Analysis (SFTA) database, a compilation of freight origin-destination survey results. The survey, not known to be duplicated by any other state, allows for the decomposition of freight flows by commodity, both northbound and southbound, thus allowing profiles to be created for seven major and minor border ports in Washington. The border ports analyzed are: Blaine/Pacific Highway, Lynden/Aldergrove, Sumas/Huntington, Oroville/Osoyoos, Danville/Carson, Laurier/Cascade, and Frontier/Patterson. Furthermore, SFTA allows for the decomposition of routes, which are used to estimate the flow of freight traffic on major Washington arterials, providing a profile of arterial highway usage by each border port. Once the profile was created, projections of northbound and southbound crossings from 2006 to the year 2015 were estimated for each border port. Linear regression trend line analysis was used to determine the potential growth of crossings based on the growth of trade between the U.S. and Canada. After projected crossings were initially estimated, projections of future northbound and southbound trade by Harmonized System of Commodity Classification Codes (HS) at the 2-digit commodity level, as well as projections of U.S. and Canadian industries, were combined with SFTA to determine the future composition of commodities crossing through the various border ports. These projections of traffic based on trade were then compared with the initial border crossing projections. The process used to determine the projections is shown in Figure 1. The top seven 3-digit NAICS commodity categories crossing the various Washington border ports are: food products, chemical products, plastic & rubber products, wood products, paper products, metallic products (fabricated and primary), and non-metallic mineral products. The NAICS categories were then translated into HS categories for 2 projections. The findings are in part corroborated with the Harmonized System trading commodities between British Columbia and Washington, as well as between Washington and Canada. The truck crossing findings show that the percentage growth in the number of northbound and southbound crossings by border port, based on 10-year average annual percent changes, range from -6.1% to 3.82%. The 10-year average annual increases for bidirectional trade range from 0.81% to 4.7%. As trade growth averages change over time, so will the commodity profiles of the specific border ports. When truck crossings are incorporated with trade growth we see a difference of 0.62% and 15.46% between the original “naïve” truck crossing projections and the new trade adjusted truck crossing projections. These projections on the future traffic volume and composition of commodities crossing between Washington and British Columbia serve as a guideline for future transportation of traded goods and the infrastructure investments necessary to support those flows.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it