Shale gas and hydraulic fracturing in South Africa: towards a petroleum legal framework that provides for innovative technologies that support energy security of supply and mitigate climate change
Bibliographic record
Abstract
It is estimated that South Africa contains vast amounts of shale gas. Meanwhile, the country relies heavily on coal as a primary energy source, as a result, it ranks amongst the highest carbon dioxide emitting countries globally, therefore is a significant contributor to climate change. Climate change is a cause for global concern, if not mitigated it will cause more severe devastation to societies worldwide. The exploitation of shale gas in South Africa will require the use of hydraulic fracturing, a technology that has generated controversy globally. The country however does not have an effective legal framework to regulate the exploration and production of shale gas using this technology. This thesis investigates whether South Africa's petroleum legal framework provides adequately for the protection of the environment against the risks posed by shale gas development. It posits that with a petroleum legal framework premised on avoiding, mitigating, and remediating environmental damage, shale gas could be developed in an environmentally sensible manner in South Africa, to enhance energy security of supply while reducing the country's carbon dioxide emissions to the atmosphere. The assessment employs the comparative legal research methodology and uses the prevention principle (avoidance), precautionary principle (mitigation), and polluter pays principle (remediation) as comparative themes. The comparative jurisdictions are South Africa, the United Kingdom, and Canada. The United Kingdom and Canada are more mature petroleum provinces/jurisdictions, therefore, have relatively advanced legal frameworks for petroleum extraction. The study finds that these principles are already embedded in the South African environmental legal framework. Therefore, the appropriate petroleum legal framework to guide shale gas development in South Africa would be one that provides for the rigorous application of these principles, in an integrated and complementary manner, with close monitoring and enforcement. The capacity of the relevant regulatory agencies will have to be enhanced to ensure effective compliance monitoring and enforcement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".