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Record W3081328457 · doi:10.35724/jies.v10i2.2399

Analisis Tingkat Ketimpangan Dan Karakteristik Sosial Ekonomi Penduduk

2019· article· en· W3081328457 on OpenAlexaboutno aff
Rafly Parenta Bano

Bibliographic record

VenueJURNAL ILMU EKONOMI & SOSIAL · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyInequalityPopulationSocioeconomicsQuarter (Canadian coin)AgricultureGeographySocioeconomic statusDemographyEconomicsEconomic growthBiologyEcologySociologyMathematics

Abstract

fetched live from OpenAlex

Although the poverty rate continues to decline, the trend of inequality in Merauke Regency tends to fluctuate and increase compared to 2007. Whereas the economic growth of Merauke Regency is consistently above 7 percent in 2011 and the contribution of the agricultural sector reaches a quarter in GRDP. In addition to the lack of research on the level of inequality in Merauke Regency, this research was conducted with the aim to find out the level of population inequality according to the World Bank's size and to understand the socio-economic characteristics of each population group. This study uses descriptive analysis to answer more clearly the purpose of this study. As a result, the level of inequality in Merauke Regency in 2017 is classified as moderate. Meanwhile, the low-income population mostly lives in the village, more likely to allocate income to consume food but less calorie, accept raskin butdid not receive a Social Protection Card. An important finding in this study is that the accessibility of low-income populations to social protection programs is still low. So it is necessary to evaluate the implementation of the program to be on target.

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 categoriesMeta-epidemiology (narrow), 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 score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.018
GPT teacher head0.203
Teacher spread0.184 · 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
Published2019
Admission routes1
Has abstractyes

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