Carbon Capital’s Political Reach: A Network Analysis Of Federal Lobbying By The Fossil Fuel Industry From Harper To Trudeau
Bibliographic record
Abstract
This paper provides a network analysis of federal lobbying in Canada by the fossil fuel industry over a seven-year period from January 4, 2011 to January 30, 2018, enabling a comparative examination of lobbying under the Harper Conservatives and the Trudeau Liberals. The network we uncover amounts to ‘small world’ of intense interaction among relatively few lobbyists/firms that control much of this economic sector and the designated public office holders in select centres of state power, who are their targets. In comparing lobbying across the Harper and Trudeau administrations, we find a pattern of continuity-in-change: under Trudeau, the bulk of lobbying has been carried out by the same large firms as under Harper, while the lobbying network has become more focused on fewer state agencies. We argue that the strategic, organized, and sustained lobbying efforts of the fossil fuel sector help to explain the close coupling of federal policy to the needs of carbon extractive corporations.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".