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Record W2212796762

HUBUNGAN KAUSALITAS ANTARA KREDIT PERBANKAN DAN TINGKAT PRODUKTIVITAS DI KALIMANTAN BARAT

2015· article· id· W2212796762 on OpenAlexaboutno aff
B Djulianus

Bibliographic record

VenueJurnal Curvanomic · 2015
Typearticle
Languageid
FieldSocial Sciences
TopicIslamic Finance and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityGranger causalityCausality (physics)Quarter (Canadian coin)Bank creditVariablesCentral bankEconomicsPanel dataValue (mathematics)Financial systemEconometricsGeographyStatisticsMathematicsMonetary economicsEconomic growthMonetary policy
DOInot available

Abstract

fetched live from OpenAlex

This research titled is Causality Relationship Between Bank Credit and Productivity Level In West The aim of this study was to obtain and analyze empirical evidence about the causality relationship between bank credit disbursed and productivity level in West Kalimantan. This study was conducted by using Granger causality test that was processed using Eviews 6.0 as tools of analysis. This research use secondary data that are bank credit and productivity data in West Kalimantan from 2005-2014 (time series) with a quarter of the data so that the amount of data observation are 40 data. The results showed a two-way causality relationship between variable of bank credit and variable of productivity level in West Kalimantan. Level of significant trust of two variables is on 5% and the probability value is smaller than the level of significant trust on 5%, so that bank credit (X) significantly affect the level of productivity (Y) and conversely the level of productivity (Y) significantly affect bank credit in West Kalimantan. Keywords: Causality, Bank Credit and Productivity Level.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.050
GPT teacher head0.312
Teacher spread0.262 · 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
Published2015
Admission routes1
Has abstractyes

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