Bibliographic record
Abstract
• Rising temperatures threaten ice road viability, shortening operational seasons and destabilizing economic activities critical to the NWT’s remote Indigenous communities. • Extended ice road seasons improve incomes in remote NWT communities, particularly benefiting economies with diversified structures. Ice road deviations disproportionately harm low-income communities reliant on resource extraction and subsistence practices, exacerbating price inflation for essentials. • Formal education negatively impacts low-income NWT families due to misalignment with traditional livelihoods and local labor markets, contrasting with its positive effects in high-income, diversified economies. • Social programs effectively support low-income households but may crowd out income-generation incentives in higher-income groups, reflecting regional inequities in economic opportunities. • Sustainable development requires culturally relevant education, targeted social policies, and climate-resilient infrastructure to address systemic inequities and ensure inclusive growth. I estimate the effects of ice road length deviation on the level of income in the Northwest Territories communities. The harsh weather conditions and extreme climates in the NWT magnify the challenges associated with maintaining infrastructure, often undermining its long-term benefits. I find that the disruptions in ice roads, which serve as vital links for northern Canadian communities, exacerbate income inequality by placing a greater burden on low-income households while disproportionately favoring higher-income groups. Education is a critical factor in driving income growth and reducing inequality. Conversely, reliance on social assistance notably reduces income for higher-income families, while it provides a boost for those in need. Larger communities, however, experience more severe economic challenges, especially within lower-income groups.
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 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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".