Environmental Aspects of Host Government Contracts in the Upstream Oil & Gas Sector
Bibliographic record
Abstract
The literature on environmental regulation of the upstream oil and gas sector in developing countries and economies in transition has focused largely on domestic legislation as well as a number of intergovernmental agreements and, more recently, voluntary industry initiatives. Much less notice has been taken of environmentally relevant content of contracts negotiated between international oil companies and petroleum producing states, which often have a significant if not dominant role in shaping the regulatory regime for oil and gas operations. The only major study on this subject, carried out by Zhiguo Gao, was published in 1994. Gao concluded that environmental issues had not received enough attention in the oil and gas contracts that he had reviewed. His conclusion raises two questions, one empirical and one normative, that this article aims to explore: (1) have environmental issues received greater attention in more recent oil and gas contracts? (2) should contracting parties give further consideration to environmental issues and, if so, in what areas and through what types of provisions? A limited survey indicates that oil and gas contracts negotiated and signed in the last fifteen years generally give greater attention to environmental protection than those signed previously, but the coverage of specific topics varies widely as does the strength of terms. Additionally, concerns that certain contractual provisions may actually undermine rather than bolster environmental protection efforts have become more prominent in the period since Gao’s study. Thus, there remains significant scope for oil and gas contracts to be improved from an environmental governance perspective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".