Adaptations of green growth and degrowth in an oil-dependent economy toward a better future
Bibliographic record
Abstract
Throughout the history of Newfoundland and Labrador (NL), the province has been relying on natural resources as the main sources of economic production. Consequently, NL is prone to external shocks from demand and price fluctuations. For example, the collapse of fisheries during the 1990s and the fall in global oil prices during the 2008 financial crisis have had negative impacts on the NL socioeconomic system, increasing unemployment and out-migration rates. A lack of modeling studies in the literature related to NL natural resources dependency, unemployment, and migration is the motivation for this research. This research focuses on studying the impact of oil, as a major natural resource for NL, dependency on other industries within the economy, employment, and migration through implementing green growth and degrowth policies as an alternative to decoupling the natural resources dependency and shifting away from the region’s historical sources of economic growth. This research links econometric, input-output (IO), and agent-based modeling techniques as a novel combination of methodologies to study the impact of an oil-dependent economy using oil prices and production reduction rates (scenarios of green growth and degrowth) as exogenous variables. The data used in this empirical analysis is obtained from Statistics Canada. The results help create suggestions for policymakers to steer socio-economic policies toward developing their economy for a better future.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".