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Record W4205559693 · doi:10.31219/osf.io/htjsp

Analisis Faktor-faktor Penyebab Migrasi Penduduk Jawa Akibat Pertumbuhan Penduduk Yang Tinggi

2021· preprint· id· W4205559693 on OpenAlex

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

Venuenot available
Typepreprint
Languageid
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Dinamika kependudukan menjadi salah satu aspek yang harus diperhatikandalam perencanaan wilayah. Kependudukan penting untuk diperhatikan dan menjadi bahan pertimbangan dikarenakan penduduk merupakan subjek sekaligus objek pembangunan guna mencapai kesejahteraan. Migrasi merupakan salah satu dari tiga faktor dasar yang mempengaruhi pertumbuhan penduduk, selain kelahiran (fertilitas) dan kematian (mortalitas).Migrasi dapat meningkatkan jumlah penduduk apabila jumlah penduduk yang masuk ke suatu wilayah lebih banyak daripada jumlah penduduk yang meninggalkan wilayah tersebut. Penelitian ini mengkaji lebih dalam dinamika migrasi penduduk yang terjadi di pulau Jawa. Penelitian ini menggunakan metode kuantitatif dengan penelitian mengguanakan Studi Literatur. Tujuan penelitian ini adalah untuk mengetahui faktor penyebab terjadinya migrasi penduduk jawa.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0030.014
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1090.007

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 head0.016
GPT teacher head0.228
Teacher spread0.212 · 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

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

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Same topicCoastal Management and DevelopmentFrench-language works237,207