The rule of competence, compensation, and workshop on employee performance mediated by prime service of public health service
Bibliographic record
Abstract
The purpose of this study was to partially analyze the effect of competence, compensation, and workshop on employee performance and the effect of competence, compensation and workshop on employee performance mediated by a prime service at the Public Health Service or Pusat Kesehatan Masyarakat (Puskesmas) in Indragiri Hulu Regency. The sample of this study was 127 employees of the Puskesmas in Indragiri Hulu Regency. The sample was taken by means of probability sampling in the form of simple random sampling using a lottery technique. Closed questionnaires were used in this study then the data taken from the questionnaires were processed using SmartPLS 3.0. The results of this study were: (1) competence has a significant effect on employee performance variable, (2) compensation has a significant effect on employee performance variable, (3) workshop has a significant effect on employee performance variable, (4) competence has a significant effect on employee performance variables mediated by a prime service, (5) compensation has a significant effect on employee performance variables mediated by a prime service, and (6) workshop has a significant effect on employee performance variables mediated by a prime service.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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".