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Record W3013804513 · doi:10.32672/jse.v5i2.1925

Analisis Pengaruh Pertumbuhan Ekonomi, IPM, Pengangguran Terbuka dan Angkatan Kerja Terhadap Kemiskinan di Sumatera Utara

2020· article· en· W3013804513 on OpenAlex
Febriangga Sembiring, Tarmizi Tarmizi, Rujiman Rujiman

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Serambi Engineering · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPovertyUnemployment rateVariablesPoverty rateUnemploymentStatisticsStatistical analysisMathematicsEconomicsEconomic growth

Abstract

fetched live from OpenAlex

<p>Poverty complexity problem is a multidimensional problem, and poverty is related to various aspects of people's lives so that efforts to solve the poverty problem are not easy. This study has purpose to determine and analyze Economic accretion effect, Human development index, Open Unemployment Rate, and Labor Force Participation Rate on Poverty in North Sumatra Province. Secondary data from 2004 - 2017 is used. Data Source is from Board of Central Statistics in North Sumatra Province with testing conducted through the classic judgement exam and statistical exam. With assist of EViews 6.0 statistical data data processing software, data analysis showed that Economic Accretion and idleness Rate variables have a positive and prominent influence on α = 10%, the Human development index variable and the Labor Force Participation Rate are not prominent at α = 10%, on poverty. Regression results are R<sup>2</sup> = 0.945055, that shows independent variable used affects dependent variable by 94.51% and the rest 5.49% is affected by other variables beyond analyzed approach.</p>

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.182
Teacher spread0.159 · 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