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Record W4386256133 · doi:10.18280/ijsdp.180822

Stakeholder Communication and Its Impact on Participatory Development Planning in Rural Areas

2023· article· en· W4386256133 on OpenAlexvenueno aff
Adhi Iman Sulaiman, Shinta Prastyanti, Tri Nugroho Adi, Chusmeru, Wiwik Novianti, Rili Windiasih, Sri Weningsih

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
FundersJenderal Soedirman University
KeywordsEnvironmental planningStakeholderCitizen journalismBusinessParticipatory planningRural developmentEnvironmental resource managementStakeholder engagementRural areaEnvironmental scienceGeographyPolitical sciencePublic relationsAgriculture

Abstract

fetched live from OpenAlex

This study delves into the dynamics of stakeholder communication within the realm of Participatory Development Planning (PDP) in rural regions, which are predominantly marked by a potent patriarchal culture.Utilizing a quantitative explanatory survey approach paired with path analysis, data was compiled from 40 local stakeholders.These respondents included representatives from the village government, as well as members of socio-economic and cultural factions within the village community.Our research underscores that the stakeholder communication processes within PDP are of high intensity, though this intensity wanes when interactions with regional government organizations come into play.Further, the study finds that the unique characteristics and aspirations of stakeholders wield significant influence over the PDP communication process.These insights offer a valuable understanding of the complexities of stakeholder communication in rural development planning, with an emphasis on the necessity to bolster communication with regional government organizations.It is inferred from the study that the quality of development planning and programs, even at a grassroots level, hinges on the competencies of stakeholders, their ability to articulate interests founded on the real needs and challenges of the community, and their capacity to transform these interests into public policy through effective communication with government organizations.

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 score0.059
Threshold uncertainty score0.319

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 head0.068
GPT teacher head0.310
Teacher spread0.242 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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