Ethical Accounting for Mineral Endowments: A Framework for Sustainable Public Finances
Bibliographic record
Abstract
ABSTRACT This article critiques the current and proposed treatment of mineral resource extraction in government finance statistics and national accounts. Mineral endowments are a shared inheritance, often held in trust for present and future generations. Current standards misclassify mineral sale proceeds as revenue rather than capital receipts, distorting public sector sustainability metrics. This creates perverse incentives for unsustainable resource exploitation while hiding significant public wealth losses. The draft SNA 2025, which includes the split asset approach, remains inadequate. Case studies from Goa, Canada, and Australia highlight these deficiencies. We propose an alternative framework that avoids premature mineral asset recognition, classifies mineral sale proceeds as capital receipts, records extraction losses as expenses, and uses Net National Income as a target metric. The proposed reforms would promote fiscal sustainability and intergenerational equity in mineral resource management, better reflecting the economic reality of mineral extraction's impact on public sector net worth and national wealth.
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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 | 0.030 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".