Grassroots Nature Reserves and Common Property Protected Areas
Bibliographic record
Abstract
"This paper argues that common property regimes can also regulate resource use by a wide variety of stakeholders in order to conserve the many non-consumptive values of nature, as do protected areas. This gap in the literature appears to exist because conservation usually implies non- use, while common property theory is usually concerned with the consumptive use of common-pool resources where 'exclusion from the resource is costly and one person's use subtracts from what is available to others' (Dietz et al. 2002: 18). Furthermore, protected areas are often regarded as a kind of institution entirely separate from common property regimes. Indeed, some advocates of local control have seen protected areas as examples of a new enclosure movement (Escobar 1995; Katz 3 1998), responsible for undermining otherwise effective systems of customary or indigenous resource governance (Peluso 1992; Neumann 1998). We share the concern for sustaining livelihoods based on local resource use and governance that motivates many of these researchers, but argue that common property theory can also be applied to resources which are not subtractable: many of the concepts, including institutions for collective decision-making, can sustain broader environmental values by facilitating non-consumptive resource use (Freese 1998). This paper will explore the potential synergies between common property theory and conservation strategy in the establishment and management of protected areas."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".