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Record W2957379617 · doi:10.31219/osf.io/ac8qp

Peran Ketua Mahkamah Konstitusi dalam Memengaruhi Putusan Mahkamah Konstitusi

2019· article· id· W2957379617 on OpenAlexaff
Ali Marwan Hsb

Bibliographic record

Venuenot available
Typearticle
Languageid
FieldSocial Sciences
TopicLegal Studies and Policies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Ketidakpercayaan pencari keadilan untuk mengajukan permohonan pengujian undang-undang ke Mahkamah Konstitusi tentu menjadi satu masalah dalam proses pencarian keadilan di Indonesia. Hanya dikarenakan Ketua Mahkamah Konstitusi diduga melakukan lobi-lobi dengan Komisi III Dewan Perwakilan Rakyat, kemudian dianggap Mahkamah Konstitusi tidak lagi objektif dalam memutuskan suatu perkara. Dalam tulisan ini kemudian akan dilihat bagaimana sebenarnya keberadaan atau peran Ketua Mahkamah Konstitusi dalam memengaruhi putusan Mahkamah Konstitusi. Dalam proses pengambilan keputusan pada Rapat Permusyawaratan Hakim, Ketua tidak dapat mendikte dan memaksakan isi putusan sebagaimana yang diinginkannya kepada hakim konstitusi lain. Hal ini jelas terlihat dalam beberapa putusan Mahkamah Konstitusi, dimana seorang Ketua Mahkamah Konstitusi kalah dalam perdebatan dalam Rapat Permusyawaratan Hakim dan mengajukan dissenting opinion. Dari hal tersebut juga dapat dilihat bahwa Ketua Mahkamah Konstitusi tidak bisa memengaruhi putusan Mahkamah Konstitusi dengan kedudukannya, melainkan dengan argumentasinya terhadap suatu perkara. Oleh karena itu, untuk menghindari adanya dugaan-dugaan lobi antara hakim konstitusi termasuk Ketua Mahkamah Konstitusi dengan lembaga negara pengusul disarankan agar proses perpanjangan masa jabatan hakim konstitusi tidak lagi dilakukan fit and proper test.

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: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0260.007

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 head0.018
GPT teacher head0.278
Teacher spread0.259 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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