Exploring the relationship between plural values of nature, human well‐being, and conservation and development intervention: Why it matters and how to do it?
Bibliographic record
Abstract
Abstract Globally, land and seascapes across the bioculturally diverse tropics are in transition. Impacted by the demands of distant consumers, the processes of global environmental change and numerous interventions seeking climate, conservation and development goals, these transitions have the potential to impact the relationships and plurality of values held between people and place. This paper is a Synthesis of seven empirical studies within the Special Feature (SF): ‘What is lost in transition? Capturing the impacts of conservation and development interventions on relational values and human wellbeing in the tropics’. Through two Open Forum workshops, and critical review, contributing authors explored emergent properties across the papers of the SF. Six core themes were identified and are subsumed within broad categories of: (i) the problem of reconciling scale and complexity, (ii) key challenges to be overcome for more plural understanding of social dimensions of landscape change and (iii) ways forward: the potential of an environmental justice framework, and a practical overview of methods available to do so. The Synthesis interprets disparate fields and complex academic work on relational values, human well‐being and de‐colonial approaches in impact appraisal. It offers a practical and actionable catalogue of methods for plural valuation in the field, and reflects on their combinations, strengths and weaknesses. The research contribution is policy relevant because it builds the case for why a more plural approach in intervention design and evaluation is essential for achieving more just and sustainable futures, and highlights some of the key actions points deemed necessary to achieve such a transition to conventional practice. Read the free Plain Language Summary for this article on the Journal blog.
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.
How this classification was reachedexpand
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".