Discourses mapped by Q-method show governance constraints motivate landscape approaches in Indonesia
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
Interpreting discourses among implementers of what is termed a "landscape approach" enables us to learn from their experience to improve conservation and development outcomes. We use Q-methodology to explore the perspectives of a group of experts in the landscape approach, both from academic and implementation fields, on what hinderances are in place to the realisation of achieving sustainable landscape management in Indonesia. The results show that, at a generic level, "corruption" and "lack of transparency and accountability" rank as the greatest constraints on landscape functionality. Biophysical factors, such as topography and climate change, rank as the least constraining factors. When participants considered a landscape with which they were most familiar, the results changed: the rapid change of regulations, limited local human capacity and inaccessible data on economic risks increased, while the inadequacy of democratic institutions, "overlapping laws" and "corruption" decreased. The difference indicates some fine-tuning of generic perceptions to the local context and may also reflect different views on what is achievable for landscape approach practitioners. Overall, approximately 55% of variance is accounted for by five discourse factors for each trial. Four overlapped and two discourses were discrete enough to merit different discourse labels. We labelled the discourses (1) social exclusionists, (2) state view, (3) community view, (4) integrationists, (5) democrats, and (6) neoliberals. Each discourse contains elements actionable at the landscape scale, as well as exogenous issues that originate at national and global scales. Actionable elements that could contribute to improving governance included trust building, clarified resource rights and responsibilities, and inclusive representation in management. The landscape sustainability discourses studied here suggests that landscape approach "learners" must focus on ways to remedy poor governance if they are to achieve sustainability and multi-functionality.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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