Defining the “Local” in Local Content Requirements in the Oil and Gas and Mining Sectors in Developing Countries
Bibliographic record
Abstract
Abstract This paper examines how the term “local” has been understood in the definitions of “local content” in selected jurisdictions in developing countries. The paper critiques the centralist approach adopted by these countries that defines local content in terms of first consideration being given to their “nationals.” Little or no thought is given to the local populations who live in the area where the resource extraction takes place. The paper argues that if policymakers do not pay close attention to how “local” is defined, the benefits of local content requirements (LCRs) may be captured by “outsiders.” A bottom-up approach that recognizes the local populations where the extractive activities take place can help developing countries to prevent or douse resource conflicts. Community frustration resulting from seeing lucrative jobs given to “outsiders” can stir up conflicts. Given that revenues from extractive resources are managed by national governments in most jurisdictions, LCRs can provide a mechanism to meet the demands of subnational stakeholders, such as local governments and communities. This will in turn enable companies to obtain the social license to operate.
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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 | 0.000 |
| 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".