Bibliographic record
Abstract
This study was undertaken to assess how the various United States (U.S.) import compliance programs in place at the Canada/U.S. border are affecting Canadian motor carriers operating into the U.S. The authors refer to these programs throughout the report as land border customs and security measures. Although some of the conclusions and recommendations contained in this report may express concerns with the application of some of these programs, there is no implied criticism of the need for enhanced security at the border. In fact, the Canadian government continues to work closely with our counterparts in the U.S. on a variety of initiatives designed to develop a border that facilitates the efficient movement of legitimate goods and people, while at the same time ensuring that the border is more secure. The Canadian trucking industry also understands full well the security imperative and continues to jointly pursue solutions with governments on both sides of the border that are “win-win ” in terms of trade and security. Transport Canada, the Ontario Ministry of Transport and the Federation of Québec Chambers of Commerce in collaboration with the Ministry of Transport Québec, provided funding for this report. In addition to the funding partners, two other provincial transportation departments- New Brunswick and Manitoba as well as two other industry associations- the Canadian Trucking Alliance and the Owner-Operators ’ Business Association of Canada participated on the Steering Committee established for this study. The opinions contained in this report are soley the responsibility of the authors, DAMF
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.639 | 0.435 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".