MODELLING LOCAL ECONOMIC IMPACTS OF WILDFIRE RECONSTRUCTION AND ENERGY TRANSITIONS IN REMOTE INDIGENOUS COMMUNITIES
Bibliographic record
Abstract
Rural and remote Indigenous communities in Canada are particularly vulnerable to wildfires and energy insecurity. These challenges are compounded by higher levels of poverty and greater geographic isolation, making it more difficult for these communities to respond effectively and build long-term resilience. This doctoral dissertation comprises three studies that develop empirical models using Input-Output techniques to assess the economic impacts of wildfires and the energy transition in northern communities. The first study examines the provincial scale economic impacts of the reconstruction of Fox Lake, one of the three reserves of Little Red River Cree in Alberta, which was destroyed by the Paskwa wildfire in 2023. The study estimates the effects of evacuation, transportation, and reconstruction expenditures by analyzing recovery expense reports from March 2023 to April 2024. Findings show that post-fire recovery expenditures increased the province’s production values, with an overall multiplier of 1.76 for total recovery spending. The federal government's $291 million contribution led to a $221 million increase in provincial production, boosting Alberta’s gross value added by $253 million and creating 2,300 full-time jobs. The second study develops a methodological tool to support policy and government intervention planning, utilizing input-output models tailored to represent local economies in remote Indigenous communities. The model modifies the technical coefficients and final demand by adjusting the intensity of leakages and margins associated with transportation costs, storage, and commercial activities. Additionally, based on the application of the methodological approach to a case study community, this study presents the economic impacts of biomass energy production in Fort McPherson, an Indigenous community located in the Northwest Territories. The third study explores the potential deployment of a micro-scale nuclear reactor in Inuvik, a remote community in the Northwest Territories. Using New Institutional Economics theory and Input-Output models at community and provincial/territorial levels, the study examines Canada’s nuclear governance framework and how economic benefits are distributed across community, territorial and provincial levels under four different ownership and operational scenarios involving the community, territorial power utility, and a private company. Results highlight that scenarios with community ownership tend to produce stronger local economic development outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".