From conflict to collaboration: Atewa Forest governance
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
Abstract The problem of forest degradation and loss has become the concern of many countries. To address this challenge, some collaborate in sustainable forest management. The most successful outcomes, however, are observed where local participation is an essential part of conservation efforts. In Ghana, forests have experienced various degrees of exploitation over the years, resulting in their ecological decline. Despite its designation as a protected area for biodiversity and ecosystem services, the Atewa Range Forest Reserve in Ghana has been significantly impacted by deforestation, illegal mining, and other destructive activities. The purpose of this paper is to examine ecologically based management approaches that could be adopted to generate beneficial outcomes for all forest stakeholders and actors in Ghana. The study sampled forest stakeholders in Kwabeng, the administrative capital of the Atewa West District, to understand forest governance challenges and outline strategies for overcoming them. The study revealed that a bottom‐up all‐inclusive approach to managing forest resources is necessary. This paper, therefore, proposes an integrated forest governance that prioritizes the UN Sustainable Development Goal 15—Life on Land‐related to forest preservation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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