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Record W4410047315 · doi:10.36733/jeco.v5i1.11535

UPAYA PENGELOLAAN LINGKUNGAN HIDUP PADA KAWASAN RAWAN BENCANA PROVINSI BALI

2025· article· id· W4410047315 on OpenAlexaff
A.A. Gde Sutrisna Wijaya Putra, Ni Luh Putu Mahendra Dewi, Shinta Maharani, Wahyudi Wahyudi

Bibliographic record

VenueJurnal Ecocentrism · 2025
Typearticle
Languageid
FieldSocial Sciences
TopicCommunity-based Tourism Development and Sustainability
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsForestryGeographyAgricultural scienceEnvironmental science

Abstract

fetched live from OpenAlex

Tekanan dan permasalahan lingkungan hidup di Provinsi Bali dari waktu ke waktu semakin kompleks bahkan meluas. Pertumbuhan penduduk yang relatif tinggi menjadi salah satu penyebab terjadinya tekanan dan permasalahan lingkungan. Pertumbuhan penduduk Bali rata-rata 1,01% per tahun pada periode tahun 2010-2020, sedangkan pada tahun 2021 pertumbuhan penduduk Bali sebesar 1,4%. Pertumbuhan penduduk tertinggi telah terjadi di Kabupaten Buleleng mencapai (2,51%) dan Kabupaten Karangasem sebesar 2,29%, sedangkan untuk Kota Denpasar dan Kabupaten Badung terjadi penurunan pertumbuhan penduduk dengan persentase -0,81% untuk Kota Denpasar dan 0,09% terjadi di Kabupaten Badung dikarenakan adanya dampak Covid-19 yang mendorong terjadinya migrasi penduduk dari wilayah perkotaan ke pedesaan sehingga terjadi penurunan pertumbuhan penduduk yang sangat signifikan. Meskipun pertumbuhan penduduk di Provinsi Bali mengalami penurunan dibanding sepuluh tahun sebelumnya, namun pengelolaan lingkungan hidup tetap harus diupayakan oleh Pemerintah bersama-sama dengan masyarakat. Namun disadari bahwa upaya pengelolaan lingkungan hidup secara “business as usual” tidak akan mampu mengimbangi laju kerusakan lingkungan hidup.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.280
Teacher spread0.270 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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