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Record W2808324029 · doi:10.38011/jhli.v1i1.10

ULASAN PERUNDANG – UNDANGAN “Potensi Undang-undang Nomor 18 Tahun 2013 dalam Mendukung Penerapan Demokrasi Lingkungan”

2014· article· id· W2808324029 on OpenAlexaff
Lakso Anindito

Bibliographic record

VenueJurnal Hukum Lingkungan Indonesia · 2014
Typearticle
Languageid
FieldSocial Sciences
TopicIndonesian Legal and Regulatory Studies
Canadian institutionsNetwork for Business Sustainability
Fundersnot available
KeywordsHumanitiesPolitical scienceLaw enforcementLawEnforcementPhilosophy

Abstract

fetched live from OpenAlex

AbstrakTulisan ini akan membahas potensi UU Nomor 18 Tahun 2013 tentang Pencegahan dan Pemberantasan Perusakan Hutan (UU P3H) dalam mendukung penegakan demokrasi lingkungan. Untuk mempertajam pembahasan, fokus kajian akan dilakukan dari dua aspek, yaitu: 1) Perangkat yang dapat didayagunakan untuk mendukung penegakan hukum yang efektif sehingga dapat melindungi hak mendasar warga negara; dan 2) Peran aktif masyarakat dalam penegakan hukum. Kedua aspek tersebut dirasa penting untuk mewujudkan nilai-nilai mendasar dari demokrasi lingkungan yang didasarkan peran aktif masyarakat dalam pengambilan keputusan terkait kebijakan penegakan hukum2 dan penerapan penegakan hukum yang adil, akuntabel dan efektif dalam rangka menjaga serta melindungi hak masyarakat atas pemanfaatan sumber daya alam.AbstractThis article will discuss the potential of Law No. 18 of 2013 regarding Prevention and Eradication of Forest Degradation in supporting implementation of environmental democracy. To sharpen the analysis, the focus of study will be conducted from two aspects, namely: 1) The tools that can be utilized to support effective law enforcement in order to protect the fundamental rights of citizens, and 2) The active role of people in law enforcement. Both aspects are considered important to realize the fundamental values of a democratic environment based on active role in decisions related to policy enforcement and application of the rule of law that is fair, accountable and effective in order to maintain and protect the people's right to use natural resources.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0410.006

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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2014
Admission routes1
Has abstractyes

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