Bibliographic record
Abstract
htrn 1 September 2005.Kompetensi profesi yang sesuai adalah "kemarnpuan bekerja yang mernenuh i standar-standar yang d iperl ukan dalam suatu pekerjaan atau profesi tertentu".Dalam suatu profesi, kompetensi tidak hanya sekedar pengetahuan, melainkan rneliputi kemarnpuan bekerja yang dilaksanakan dalam suatu profesi tertentu.Ada dua jenis kompetensi, yang pertama adalah kompetensi jelas, yaitu kornpetensi yang mudah dibentuk dan terlihat jelas, dan yang kedua adalah kompetensi lunak, yaitu kompetisi yang perlu waktu lama untuk dibentuk, karena bersifat tersernbunyi.Misalnya kompetensi seorang sekretaris terdiri dari qneka pengetahuan dan keterarnpilan teknis kesekretariatan yang mudah terlihat, narnun meliputi kornpetensi lunak, antara lain orientasi pad a pelanggan, berpiki r anal it is dan konseptual, serta fleksibilitas dalam bekerja.Lebih lanjut jenis kompetensi juga bisa
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.667 | 0.689 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".