Private Forest Governance, Public Policy Impacts: The Forest Stewardship Council in Russia and Brazil
Bibliographic record
Abstract
Under what conditions do private forest governance standards influence state policy and behavior to become more oriented toward sustainability? We argue that governance schemes targeting firms may indirectly shape state behavior, even when designed to bypass state regulation. Through an examination of the Forest Stewardship Council (FSC) in Russia and Brazil, we find that the FSC has influenced domestic rhetoric, laws, and enforcement practices. FSC has had a more disruptive and consequential impact on Russia’s domestic forest governance; in Brazil, earlier transnational environmental campaigns had already begun to shift domestic institutions toward sustainability. Based on interview data and textual analysis of FSC and government documents, we identify the mechanisms of indirect FSC influence on states—professionalization, civil society mobilization, firm lobbying, and international market pressure, and argue that they are likely to be activated under conditions of poor and decentralized governance, overlapping and competing regulations and high foreign market demand for exports.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".