A Model of Climate Governance:Canada's Interorganizational Complex Framework
Bibliographic record
Abstract
How should we think about Canada’s climate governance? My claim is that we should think about Canada’s climate governance as an interorganizational complex of state and non-state governance. State and non-state governance are broad labels for making sense of the concept of governance from the perspective of the role government plays, but the lack of consensus on what governance means makes their boundaries debatable. Nonetheless, we can frame these labels within the theoretical governance discourse. Building on the taxonomy of Baldwin, Scott, and Hood, I frame state and non-state governance as degrees in a continuum with pure command-and-control (CAC), involving not only administrative regulation but also market regulation and litigation, and the broader concept of social control, which infers the self-governance capacity of a social group, at the extremes. Varying degrees of state and non-state governance would appear along this continuum. I introduce CAC and social control below, then apply them to Canada to answer my central question and build my claim.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".