Using the capability approach to analyze contemporary environmental governance challenges in coastal Brazil
Bibliographic record
Abstract
Conservation and development are often framed as a dichotomy, requiring trade-offs. But trade-offs can be due to the particular political situation and to relationships of domination, and are not necessarily the inevitable result of intractable situations. Amartya Sen’s capability approach, which centers on human development, has enjoyed increasing applications in the environment area, but little in the commons literature. This article applies the capability approach framework to analyze human development in Trindade, Brazil, by answering key questions that are central to this approach (1) What kind of lives are people able to live? Are they able to be or do what they have reason to value? and (2) What is the quality of economic, social and political relations in Trindade? Three main 'shocks' emerge: (a) Conflict with external commercial developers, (b) Paving of access road into community, and (c) Enforcement of protected area regulations on historical community land and sea space. Capability priorities were established for women, men, older adults, and people with disabilities. The impacts of development and conservation policies are different for the four groups, as are the priorities for capabilities. The case demonstrates that space for public participation is not sufficient to ensure that the people who are trying to improve their wellbeing, and be the author of their own lives, can influence the outcome. It also shows that regular contact through public participation does not necessarily create empathy, as Sen assumed in The Idea of Justice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".