Rights to do, rights to prevent, and an intersected approach? Lessons from intellectual property, information control and oil and gas
Bibliographic record
Abstract
This chapter explores IP and oil and gas frameworks particularly in the UK and in Canada, and the different approaches taken to information sharing and some litigation at national level and through Investor State Dispute Settlement. This chapter notes that the existence of clear goals of a regulatory system, an assertive regulator with robust enforcement powers, and industry support for new regulatory approaches may seem to have created oil and gas regimes which can prevail over IP rights when the two fields clash in respect of information of sharing and re-use. It is suggested that the two sets of decision makers are in fact taking a blinkered, or at least incomplete, approach to addressing this apparent battle of equals. This chapter then builds arguments which can have an impact on all regulatory and legislative actions to address a public goal when the response (properly viewed) involves more than one policy area and field of law, and also involve private rights.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.056 |
| Scholarly communication | 0.018 | 0.023 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 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".