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Record W2284976277 · doi:10.5539/ijef.v8n2p234

The Influence of Economic Growth on the Degree of Autonomy of the Regions and the Absorption of Labor and Social Welfare: Regencies and Cities of Maluku Province

2016· article· en· W2284976277 on OpenAlexvenueno aff
Nahu Daud

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)AutonomyWelfareRegional autonomyTest (biology)Path analysis (statistics)EconomicsEconomic growthPolitical scienceMathematicsStatisticsLaw

Abstract

fetched live from OpenAlex

This research aims (1) to analyze and test the influence of economic growth on the degree of autonomy the area in County Government and city of Maluku Province, (2) Analyze and test the influence of economic growth on the absorption of labor on County Government and city of Maluku province (3) Analyze and test the influence of economic growth on the welfare of society at the County Government and the city of Maluku province (4) Analyze and test the influence of degree of autonomous region of absorption of labor on County Government and city of Maluku province, (5) Analyze and test the influence of the degree of autonomy the area of social welfare in the Government District and the city of Maluku province (6) Analyze and test the influence of absorption of labor against the welfare of the community on County Government and City Maluku province. The approach used is the analysis of Path Analysis, intended to answer a relationship direct or indirect causal model has been developed on the basis of theoretical consideration of researchers and certain knowledge. In addition to the causal relationship is based on the data, also based on knowledge, the formulation of hypotheses and logical analysis, so that it can be called path analysis can be used to test a set of causal hypotheses as well as to interpret these relationships. The results showed (1) economic growth positively and significantly influence the degree of autonomy of the region. These results lend support to the hypothesis of one stating that economic growth was a significant influence on the degree of autonomy of the region. (2) The influential economic growth positively and significantly to labor absorption. These results lend support to the hypothesis of two stating that the influential economic growth dramatically to labor absorption. (3) Economic growth positively and significantly influences the well-being of the community. These results provide support for the three hypotheses which state that the economic growth affects significantly to the well-being of society. (4) The degree of autonomy the positive and significant effect of absorption of labor. (5) The degree of autonomy to the region in a positive and significant effect on the welfare of society. (6) The positive impact of labor absorption and significantly to the well-being of society. (7) The results of the discussion to confirm that economic growth affectsconsiderably to the well-being of the community through the degree of autonomy of the regions and the absorption of labor. Significant influence occurs because the existence of a direct relationship with the role of the community.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.358

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.205
Teacher spread0.179 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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