ASSESSING THE FULL COST OF ENERGY IN NOVA SCOTIA: A GPI ATLANTIC APPROACH
Bibliographic record
Abstract
The extraction, production, transportation, marketing and use of energy have effects on peoples ’ health, the environment, and society. Few of these effects are reflected in the market price of energy. The GPIAtlantic Energy Accounts identified and attempted to measure the sustainability and full cost of the current energy system based on “full-cost accounting ” principles. Twenty-nine indicators covering socio-economic, health and environment, and institutional considerations were presented in the full report. This paper represents a summary of this study, focusing on the full cost analysis of energy in Nova Scotia. Only air emissions and greenhouse gases had all the data required to conduct a full cost analysis. The analysis of the damage costs associated with Nova Scotia’s energy sector in 2000 resulted in a low estimate of over $ 444 million, and a high estimate of almost $4 billion. These aggregate cost estimates represent only a small fraction of the true costs of energy as these do not include cost impacts associated with energy affordability, reliability, security, resource costs, subsidies, land use, and land and water contamination. Despite the exclusions, limitations and difficulties of costing exercises, the very act of considering the full costs of energy is extremely important. The endeavour of attempting to estimate the costs of goods and services allows the consideration of costs that are outside of our traditional accounting system, and therefore not reflected in decision-making. The information presented here can be used by Nova Scotia (and others) to actively pursue a more sustainable energy sector.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".