AIR ACCESSIBILITY IN NORTHERN CANADA: PROSPECTS AND LESSONS FOR REMOTER COMMUNITIES
Bibliographic record
Abstract
This paper assesses the impact of Canada's air transportation policy on air accessibility of remote and arctic communities in a context of liberalization of the aviation industry. The central objective is to examine policy's impact on essential air service – travel and shipment. An observational study of the federal government's National Airports Policy (NAP) of divesting smaller airports to local entities is conducted using airport cases both inside and outside the National Airports System (NAS) covering 12 communities in Ontario (Ont.), Manitoba (Man.), British Columbia (B.C.), Quebec (Que.), the Northwestern Territories (NWT), and Yukon Territory (YT). The paper also evaluates the impact of Airports Operations and Maintenance Subsidy Program (O&MSP) and investigates the impact of several federal government departments in assuring air accessibility to remote areas. It is argued that: (a) local management allows for greater entrepreneurship and leads to some efficiency gains, (b) remote and arctic airports seem to be unable to sustain and operate their infrastructures without receiving local or federal contributions, and (c) Health Canada, Indian and Northern Affairs Canada (INAC), and Inuit organizations, such as the Makivik Corporation through its subsidiaries carriers First Air and Air Inuit, play a significant role in making air travel accessible. It concludes that, although the decentralization strategy and the subsidy mechanisms are benefiting remote communities, Canada's policy success is constrained by its failure to incorporate changing conditions, loss of focus, and flaws in performance evaluation. Keywords: National Airports Policy (NAP), Remote airports, Arctic airports, Inuit organizations, Health Canada, Indian and Northern Affairs Canada (INAC), Canada.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".