Environmental impact assessment: evidence-based policymaking in Brazil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Environmental impact assessment (EIA) procedures aim prospectively to collect evidence about the environmental impacts of economic projects and to avoid or compensate for the costs incurred. This article asks whether such procedures have been effective in Latin America after many regional countries returned to some version of the developmental state after 2000. It does so by surveying the procedural effectiveness of Latin American regulations comparatively before turning to a deeper study of the Brazilian case. In Brazil, which has some of the strongest EIA procedures in the region, it finds that stakeholders make very different assessments of its effectiveness, not least because they define the standard differently. Economic actors in and out of the state criticise Brazilian EIA as ineffective from a transactive standpoint, which questions the time and cost associated with environmental licencing. Environmental and community activists see EIA as ineffective in achieving the substantive sustainability ends they value. Neither appreciates the procedural improvements offered by licencing professionals. The article concludes that EIA invites a broader set of stakeholders than did classic developmental states, but cannot on its own adjudicate among the resulting multiple visions of how to carry out development strategies.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it