Perencanaan Suksesi: Urgensi, Model, dan Implementasi
Bibliographic record
Abstract
Buku kategori manajemen perusahaan yang berjudul Perencanaan suksesi: urgensi, model, dan implementasi merupakan buku karya dari Betty Riadini, Abdul Bari. Buku ini membahas terkait suksesi yang dilakukan dalam suatu organisasi, baik perusahaan, pemerintah, maupun organisasi lainnya. Buku ini berisi sebelas bab pembahasan yang terbagi menjadi tiga bagian. Bagian 1 terdiri atas 2 bab: Urgensi Perencanaan Suksesi dan Peran Perencanaan Suksesi; bagian 2 terdapat 7 bab: Model Perencanaan dan Manajemen Suksesi, Pertimbangan Isu dan Kendala Perencanaan Manajemen Suksesi, Membangun Pensejajaran Strategis, Mengidentifikasi Target Suksesi dan Menganalisis Talent Pool, Pengembangan Perencanaan Suksesi, Implementasi Metode Suksesi, dan Penyesuaian Penerus/Suksesor; bagian 3: Evaluasi Strategi Suksesi dan Membangun Komitmen Pengembangan.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.293 | 0.207 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".