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Record W7126371753 · doi:10.1177/14649934251413867

Integrated Landscape Approaches: A Pathway Towards Just Sustainable Development?

2025· article· en· W7126371753 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProgress in Development Studies · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransformative learningOperationalizationNegotiationEconomic JusticeSustainable developmentCapability approachPower (physics)Sustainability

Abstract

fetched live from OpenAlex

Landscape approaches mobilize stakeholders across sectors and scales to negotiate development–conservation trade-offs and land-use allocation. Building on the concept of earth system justice, we examine how efforts to operationalize such approaches in Ghana, Zambia and Indonesia advance landscape justice. We observed contributions to procedural, recognitional and intergenerational justice, while interspecies justice remains overlooked. Yet, power asymmetries, exclusionary practices and institutional constraints hinder progress towards intragenerational and substantive—distributive, corrective, restorative and transformative justice. In contexts lacking commitment to transformative change, trade-offs are inevitable. Pursuing incremental change rather than ‘perfect’ justice may represent a second-best but more realistic pathway towards just landscape governance.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.054
GPT teacher head0.258
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it