Revising Theories of Nonstate Market-Driven (NSMD) Governance: Lessons from the Finnish Forest Certification Experience
Bibliographic record
Abstract
We assess the ability of Cashore, Auld, and Newsom's theoretical framework on “Nonstate Market-Driven” (NSMD) governance to explain the emergence of and support for forest certification in Finland. In contrast to Sweden's experience, the environmental group-initiated international forest certification program, the Forest Stewardship Council (FSC), failed to gain significant support. Instead, the commercial forest sector created and adopted the Finnish Forest Certification Program, which domestic and international environmental groups ultimately rejected as inadequate. The NSMD framework must better incorporate two key findings. First, the dependence of international markets on the targeted country's forest products can shape domestic certification choices. We found that the largely non-substitutable qualities of Finnish paper products gave the domestic sector greater leeway in responding to international pressures. Second, whether the FSC is being championed primarily to influence a country's domestic forestry debates or indirectly as a lever with which to improve forest practices elsewhere appears to permeate the forest sector's overall receptiveness to the FSC.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".