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Record W2472692758 · doi:10.15294/jejak.v4i1.4640

PENGEMBANGAN SEKTOR UTAMA REGIONAL PENDEKATAN EFISIENSI TEKNIKAL DAN SIKLUS BISNIS Studi Kasus di Propinsi Bali

2015· article· en· W2472692758 on OpenAlexaboutno aff
Agni Alam Awirya

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness cycleEconomic sectorQuarter (Canadian coin)FrontierEconomic efficiencyAgricultureEconomicsBusinessEconomyMarket economyMacroeconomicsGeography

Abstract

fetched live from OpenAlex

<p class="IsiAbstract"><span>The appropriate resource allocation on potential economic sectors can spur a faster economic growth. Knowledge on economic sectors which are efficient and have experiencing positive business cycle could ease the allocation of available economic resources. This research provides information on the technical efficiency of economic sectors as well as the business cycle of the economy in Bali. A stochastic frontier method is used to analyze the technical efficiency of economic sectors while the Bry-Boschan algorithm is used to estimate the business cycle of the economic sectors which are relatively efficient. The estimation result indicates that the efficient economic sectors in Bali are trade, hotel &amp; restaurant (thr) sector and agriculture sector. Both sectors contribute most on the Bali’s economic output. At the end of the observation period, the economic business cycle in Bali is in a period of contraction. It is estimated that the next quarter will be the expansion period.</span>

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0030.001
Research integrity0.0000.001
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 head0.420
GPT teacher head0.488
Teacher spread0.068 · 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 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
Published2015
Admission routes1
Has abstractyes

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