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TANGGUNG JAWAB PEMERINTAH DAERAH PADA PENEMPATAN DAN PERLINDUNGAN TENAGA KERJA INDONESIA MENUJU NEGARA KESEJAHTERAAN

2016· article· id· W2581230929 on OpenAlexaff
Dian Ferricha

Bibliographic record

VenueAhkam Jurnal Hukum Islam · 2016
Typearticle
Languageid
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsRepatriationAutonomyIndonesian governmentIndonesianGovernment (linguistics)Social protectionWork (physics)Economic growthRegional autonomyBusinessPolitical scienceEconomicsLawEngineeringPolitics

Abstract

fetched live from OpenAlex

Ahkam: Jurnal Hukum Islam is a scientific journal contains original works from lecturers, researchers, students and other concerned parties who have not been published or are not on the publication in the form of articles on the research and conceptual ideas on the subject of islamic law. This journal publishes twice in a year on July and November, which spread throughout Indonesia and South East Asia in printed and online. Published by Faculty of Sharia and Law (FASIH), State Islamic Institute (IAIN) Tulungagung, East Java, Indonesia.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.005

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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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 designQualitative
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

Citations5
Published2016
Admission routes1
Has abstractyes

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