Sustainability and Depletion Accounting: A Case Study of Oil in Libya
Bibliographic record
Abstract
There is a strong need to study sustainability and depletion accounting of oil in the Libyan economy because oil production and export is the single largest source of national income in the country. This study covers the time period from 1990 to 2009. Throughout this period, the Libyan national economy used its oil and petroleum industries to increase national income. Development sustainability can be defined as investment divided by GDP. This measure provides an indication of the low level of sustainable development in Libya over the period of analysis, which is 0.38 on average. It is important that the Libyan government develop and implement plans and strategies for achieving sustainability and the maintenance of oil resources.Carbon dioxide emissions provide another indication of the presence or absence of sustainability. The ratio of carbon dioxide ranged from a minimum of 8.50 metric tons per capita in 1990 to 10.00 metric tons per capita in 2009 and average 9.07 metric tons per capita over the course of the study period. CO2 emissions were also much higher than other countries in the Middle East and North Africa. This suggests there was relatively little interest in the sustainable development of the Libyan economy during this period. The Environment Domestic Product (EDP) increased sharply from the beginning of the study at $24.23 billion in 1991 to $45.87 billion in 2009 in constant dollars. Again, one can infer that policy makers did not consider the depletion of oil resources and the environment in their planning process, or at least did not place a high level of concern on this issue.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".