A Voice for Change? A Network Analysis of Equity Ownership in Canada’s Fossil Fuel Industry
Bibliographic record
Abstract
Financial actors may exert considerable influence over the governance of fossil fuel corporations, which bolster or impede steps towards climate action. However, the influence of financial actors on climate instability remains to be examined. This network analysis of equity ownership uncovers the structure of control of financiers in Canada’s fossil fuel industry and examines how sensitive the industry is to major stockholders. The results infer that ownership and influence are concentrated among a small subset of predominantly foreign and corporate equity owners. Moreover, the collective influence of just 14 major stockholders is significant. Finally, high debt loads of fixed assets make fossil fuel companies particularly sensitive to their shareholders. The results infer that these major stockholders will be unlikely to use their voice to curtail carbon emissions. Thus, this study not only allows us to identify key financial actors but map their influence over the economic activities directly associated with climate stability. The paper contributes to theory and practice, bridging the literature on corporate governance, equity ownership, and climate stability.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".