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Record W4411397699 · doi:10.18280/ijsse.150406

Political Dynamics of Innovative Policy Development in Managing Forest Fires in Riau Province

2025· article· en· W4411397699 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Safety and Security Engineering · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsnot available
FundersUniversitas Islam Riau
KeywordsPoliticsDynamics (music)Environmental planningPolicy developmentBusinessEnvironmental resource managementPolitical scienceEnvironmental sciencePublic administrationSociology

Abstract

fetched live from OpenAlex

This research examines the influence of political dynamics on the development of forest fire management policies in Riau Province, Indonesia, which is a serious environmental problem with broad impacts on ecosystems, health, and the economy.In the context of this research, innovative policy refers to public policies that contain new approaches or creative solutions that differ from conventional practices in their formulation, implementation, and evaluation.These policies aim to increase the effectiveness of forest fire management and strengthen community participation and collaboration between stakeholders.Using a qualitative approach, data was collected through in-depth interviews, observation, and analysis of policy documentation and historical data.This study involved 15 key informants selected purposively based on their strategic involvement.The informants comprised four local government officials, three legislative members, four environmental NGO leaders, and four local community representatives.The main findings in this research show that interactions between several political actors, such as the government, legislature, NGOs, and the private sector, strongly influence forest fire management policies in Riau Province.Although local governments have implemented policies such as Regional Regulation Number 1 of 2019 and the Fire Control Task Force, budget fluctuations and changes in political priorities ahead of elections often affect the effectiveness of these policies.The involvement of the legislature and the private sector has positively impacted technical and financial support and a negative impact on short-term political interests.Policy sustainability relies heavily on balancing political interests with environmental protection.To achieve this, innovative policy development can be carried out through strengthening multi-actor collaboration, utilizing advanced technology such as satellite monitoring, and accurate data-based policies, which enable more targeted interventions and more efficient responses to political dynamics and long-term sustainability.In conclusion, the success of forest fire management in Riau depends on the ability to maintain policy consistency despite changes in political dynamics, as well as the importance of strengthening multi-actor collaboration and utilizing technology in formulating sustainable and effective policies.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.136

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 head0.004
GPT teacher head0.209
Teacher spread0.205 · 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