Bibliographic record
Abstract
Begun in 2011 as an internal research tool for the development of the Extractive Resource Governance Program, this study seeks to answer the vital question: Where in the world are Canadian oil and gas companies? To answer this question, we extract firm-level information from publicly traded Canadian companies in order to establish the location of their activities around the globe.1 The data collected in the “Where in the World” (hereafter WIW) project are presented through a publicly accessible interactive world map, which allows users to explore a specific country or region over time. This map can be accessed online at http://www.policyschool.ca/research-teaching/teaching-training/extractiveresource-governance/ergp-map/. For background information regarding the WIW project, including an extensive overview of the methodology, please refer to http://www.policyschool.ca/wp-content/uploads/2017/06/Where-in-the-WorldHojjati-Horsfield-Jordison-final.pdf. For a summarized overview of the annual data gathered in 2011, please refer to http://www.policyschool.ca/wp-content/ uploads/2017/06/2011-Where-in-the-World-Hojjati-Horsfield-Jordison-final.pdf. This report, as in the earlier report in this series, presents an extensive account of the global presence of Canadian oil and gas (hereafter O&G) companies in the 2012 year of study.2 In total, 228 Canadian O&G companies conducted operations in 85 countries in 2012, extending their presence to every region of the world. While North America continued to serve as the primary destination for Canadian exploration and production activities, the role of Canadian O&G service companies increased significantly in the Middle Eastern oil and gas industry, particularly in the United Arab Emirates, Saudi Arabia, Kuwait, and Oman. This report begins with a regional overview of the international activities of Canadian exploration and production (E&P) companies, followed by a summary of the level of activities on a country basis. The report then continues by providing the same analysis for Canadian O&G service companies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".