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Record W2079644210 · doi:10.1080/14888386.2010.9712647

Prospects for mainstreaming ecosystem goods and services in international policies

2010· article· en· W2079644210 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

VenueBiodiversity · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsInternational Institute for Sustainable Development
Fundersnot available
KeywordsMainstreamingPovertyGoods and servicesMainstreamEcosystem servicesPoverty reductionEnvironmental resource managementPolitical scienceEconomic growthEconomicsEcosystemEconomyEcology

Abstract

fetched live from OpenAlex

Abstract Although most management decisions affecting ecosystem goods and services (EGS) are made at a local level, these local decisions are conditioned by national and international policies. International policy domains provide clear opportunities to mainstream (integrate) EGS in ways that can support poverty reduction. However, positive poverty reduction and EGS outcomes cannot be taken for granted. Mainstreaming EGS needs careful consideration because many of the opportunities identified can reduce poverty, but may have the opposite effect if poorly managed or implemented. A major challenge is to ensure consistent policies across scales and policy domains based on analysis of the local situation. In order to support poverty reduction it matters how the mainstreaming is done and who benefits locally. Based on an analysis of EGS delivery and poverty reduction in drylands, tropical forests and coastal areas in the tropics, this paper analyses the prospects of mainstreaming EGS in a number of relevant international policy domains including: i) development assistance; ii) trade; iii) climate change and; iv) international financial institutions. For these policy domains it is analyzed how mainstreaming EGS can contribute to reaching poverty reduction and development goals, what relevant policy tracks for mainstreaming EGS exist, and what priority issues should mainstreaming focus on. The paper next provides an overview of possible tools and mechanisms for mainstreaming and ends with conclusions on what the role of the CBD can be in mainstreaming.

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)0.000
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 score0.055
Threshold uncertainty score0.481

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 head0.008
GPT teacher head0.194
Teacher spread0.186 · 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