Financing and Funding Approaches for Establishment, Governance and Regulatory Oversight of the Canadian Northern Corridor
Bibliographic record
Abstract
Multimodal, multijurisdictional corridors are highly complex, long term infrastructure projects. It is not surprising, therefore, that they often fail to get implemented. The limited evidence suggest that they can get built when a single entity— usually a national government—assembles the rights of way and provides corridor access to various infrastructure providers. Specifically, that entity has to carry out the following steps: (1) assemble the required rights of way from all those currently holding the property rights; and (2) decide on the allocation of at least usage property rights to different kinds of infrastructure providers (and ultimately users of that infrastructure). This entity, which we refer to as the Assembler, could be the federal government or a consortium that also includes sub-national levels of government. Because First Nations and other indigenous groups in Canada have constitutional or at least quasi-constitutional status, they might also have a role in a consortium.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".