Is Forest Certification a Hegemonic Force? The FSC and its Challengers
Bibliographic record
Abstract
Certification initiatives are an innovative response to both a perceived governance gap in industry regulation and the demands made on industry by civil society groups. They develop criteria for sustainable practices along supply chains, monitor compliance, and reward acquiescent firms by mitigating reputational risks and differentiating products for environmentally conscious consumers. They seek to accomplish this with minimal cost to taxpayers, nominal disruption to trade, and trivial cost to the private sector in terms of fees or inefficiencies. This article examines the Forest Stewardship Council (FSC) certification scheme as an example of the move toward nonstate, market-driven environmentalism. By utilizing a critical, Gramscian approach, it finds that while the FSC can be seen as embedded in, and furthering the agenda of, the neoliberal political economy, a close comparison to rival, producer-backed schemes exposes its antihegemonic underpinnings.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.047 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| 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".