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Record W4224305389 · doi:10.31407/ijees12.309

ROLE OF VILLAGE ORGANIZATION IN THE SUSTAINABLE MANAGEMENT OF NATURAL RESOURCES AND THEIR CONSTRAINTS IN VILLAGES (LILOWNAI, CHORBUT AND NOREPEZW) OF DISTRICT SHANGLA, KPK PAKISTAN

2022· article· en· W4224305389 on OpenAlexaff
Ahmad Zamir, Aziz Ullah, Arz Muhammad Umrani, Shehla Sattar, Rahib Hussain, Syed Talha Kamil, Shabir Ahmad Jan

Bibliographic record

VenueInternational Journal of Ecosystems and Ecology Science (IJEES) · 2022
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNatural resourceNatural (archaeology)BusinessNatural resource managementSustainable developmentResource (disambiguation)Environmental planningEnvironmental resource managementGeographyPolitical scienceEconomicsLaw

Abstract

fetched live from OpenAlex

The paper is presented to study the village organisations in the three villages of Lilownai, Chorbut and Norepeza. These village organization (VO) are involved in hill side management, being their major Natural resource. Apart from hill side management, these VO are also working on village development as a whole. These VO will be under taken various developmental activities in their villages, through donor financial support on cost share basis as well as on self-help basis. These VO are implementing the "Nagha" system for the protection of their hill side, till now, even after the withdrawal of SRSP assistance since July/2006 and have employed Chowkidars on self-help basis. All the villages are diverse in land use and type having different categories of stakeholders for Natural resource. The study conducted to explore the role of these village organizations in conservation of natural resources in the study area. The main objectives of this study were to: Compare the role of Village Development Communities Lilownai (VDCs) in sustainable management of natural resources with the past tradition systems. The constraints explored of VDCs Lilownai in Natural Resourse Management.

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)0.001
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 score0.073
Threshold uncertainty score0.211

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.190
Teacher spread0.188 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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