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Record W2035775203 · doi:10.1505/146554813807700074

Fiscal policy and its implication for community forestry in Nepal

2013· article· en· W2035775203 on OpenAlex
Ambika Paudel, Gerhard Weiss

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

VenueThe International Forestry Review · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCommunity forestryForestryFiscal policyEconomicsNatural resource economicsGeographyForest managementMacroeconomics

Abstract

fetched live from OpenAlex

SUMMARY This paper reviews the existing forest policies in Nepal mainly focussing on the fiscal policy of Community Forestry (CF), and discusses some of the existing and potential issues on the implication of fiscal policy. The review shows that Nepalese CF has some unclear and inconsistent legal provisions related to fiscal policy. The semi-structured interviews and focus group discussions with individuals from governmental and non-governmental organizations, Community Forest User Groups (CFUGs) from Parbat, Baglung and Dolakha districts of Nepal, and forest product traders from these districts demonstrate that there are a number of issues and challenges related to fiscal policy that have affected the promotion of sustainable and market-oriented management of forest resources. These issues and challenges have a direct impact on CFUGs to optimally benefit from their forest resources. As several stakeholders (including non-governmental organizations) are involved in implementation of CF program and yet do not have a direct influence on policy formulation, good coordination among government units, CFUGs and non-governmental organizations and their active involvement in the policy-making process could help to address the practical issues and challenges related to CF policy. This in turn would help to develop the policy consistent and unambiguous.

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 score0.051
Threshold uncertainty score0.420

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 head0.035
GPT teacher head0.283
Teacher spread0.248 · 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