Strategic responses to sustainable development in the Canadian oil and gas industry
Bibliographic record
Abstract
The purpose of this research is to explore the social and environmental forces affecting oil and gas producers in Canada today, and the strategic firm level and industry level responses. The research examines two leading Canadian firms in detailed case studies, as well as range of industry participants and their industry association, the Canadian Association of Petroleum Producers. The research addresses aspects of firm level strategy and competitive advantage that are emerging as the socio-political environment has become more complex and salient to firms. Limitations to previous research are addressed in the areas of theories of the firm, stakeholder theory, and law. The main findings are that the firm level competencies and resources must be viewed in the context of both natural resource scarcity and social resource scarcity. Furthermore, firms and institutions require dynamic networks extending beyond the industry structure if they are to succeed in interpreting and responding to the business environment. Those networks involve not only the exchange of knowledge, but a challenging of assumptions, or "reflexive" sense-making, much like that advocated by legal theory in the field of reflexive law. This research presents a model of stakeholders and knowledge creation that incorporates reflexive management processes. This research also presents models of "interests-based" firms driven by the need for legitimacy, and new views regarding value creation in a natural and social resource constrained environment.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".