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Record W3049295403 · doi:10.1111/sjtg.12336

An island in transition: governing conservation and development in Seram, Indonesia

2020· article· en· W3049295403 on OpenAlexaff
James Douglas Langston, Rebecca Anne Riggs, Agni Klintuni Boedhihartono, Agustinus Kastanya, Jeffrey Sayer

Bibliographic record

VenueSingapore Journal of Tropical Geography · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsWestern Forest ProductsUniversity of British Columbia
FundersCritical Ecosystem Partnership Fund
KeywordsVisionCorporate governanceSustainable developmentTransaction costScale (ratio)Environmental resource managementPolitical scienceBusinessEnvironmental planningSociologyEconomicsGeographyManagement

Abstract

fetched live from OpenAlex

Seram is Indonesia's 8th largest island. It is central to the historic spice islands, once a hotbed for international trade of profitable tree‐products, primarily clove and nutmeg. Recent increased rates of social and ecological change, including costly conflicts, present Seram with new challenges and opportunities for conservation and development. Using place‐based transdisciplinary research methods, we diagnose the problems emerging in Seram. Engaging with actors across multiple scales and sectors, we explore drivers of change, social‐ecological impacts, and institutional arrangements that might achieve improved inclusive and sustainable development outcomes. Traditional and formal governance arrangements require harmonizing to optimize the benefits and costs from large‐scale investments arriving in Seram. Organizations wishing to achieve positive impact can more strategically engage with the broad range of actors to harmonize divergent visions for the future and confront the reality of incoming investments and infrastructure.

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 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)0.000
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 score0.005
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.195
Teacher spread0.183 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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