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Record W4404374393 · doi:10.31869/mi.v18i2.5895

Peran Stakeholder Di 11 Kampung Tematik Kota Padang

2024· article· id· W4404374393 on OpenAlexaff
Harne Julianti Tou, Mutia Anggelina Putri, Denny Denny

Bibliographic record

VenueMenara Ilmu · 2024
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsStakeholderPolitical scienceLaw

Abstract

fetched live from OpenAlex

Berdasarkan Keputusan Wali Kota Padang Nomor 286 Tahun 2021 tentang Lokasi dan Tema Kampung Tematik Kota Padang Tahun 2021-2024 menetapkan 11 kampung tematik di Kota Padang yang tersebar di tiap kecamatan. Tujuan kajian ini untuk mengetahui peran stakeholder di masing-masing kampung tematik yang ada di Kota Padang. Metode analisis yang digunakan dalam kajian ini yaitu metode kualitatif dengan analisis deskriptif dan komparatif berdasarkan indikator peran pemerintah, perguruan tinggi dan CSR. Untuk melakukan analisis tersebut dilakukanya pengumpulan data sekunder berupa program kegiatan dari pihak terkai. Hasil kajian ini yaitu didapatkan bahwa stakeholder di kampung tematik ini 75% telah berperan aktif untuk mengembangkan kampung tematik, peran yang diberikan berupa program kegiatan seperti sosialisasi, pelatihan kepada masyarakat dan bantuan lainya. Untuk mensinergikan peran semua stakeholder ini perlunya suatu dokumen atau produk perencanaan pada masing-masing kampung agar dapat menjadi acuan atau rencana induk dalam pembangunan suatu kawasan, contoh dokumen perencanaan ini seperti masterplan dan DED (Detail Enginering Design) sehingga dapat dinilai apakah indikasi program yang direncanakan sudah terlaksana atau belum dan sudah berapa persen terlaksana. Kata Kunci: Kampung Tematik, Kota Padang, Peran Stakeholder

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.004

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 head0.056
GPT teacher head0.223
Teacher spread0.168 · 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
Published2024
Admission routes1
Has abstractyes

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