Outsourcing Practices in State-Owned Enterprises: Evidence From Indonesia
Bibliographic record
Abstract
This study is subject to find the factors that cause the inability of the Government in determining the type of work in the job chartering (outsourcing) by the Business Sector Association to create a flow of work activities. The authority of the Business Sector Association in making the flow of activities that determine itself the type of core work (core business) and supporting work (non-core business) when violations occur so it needs to be limited by the Government through agencies that are experts in their fields. This research method used a socio legal approach since it involved a reciprocal relationship between law and related social institutions. This research is considered as a descriptive study that described the object studied in several companies of State-Owned Enterprises (SOEs) that applied outsourcing practices in the city of Semarang. The results of the study found that the practice of outsourcing in the city of Semarang has identified several violations namely the existence of the Business Sector Association in determining the type of core work (core business) to be a supporting work (non-core business) so that it violated Article 65 paragraph (3) of Law Number 13 Year 2003 concerning The Employment. The inability of the Government in outsourcing practices is dominated by corporate strategy factors through the Business Sector Association in making the flow of activities that should use the outsourcing system for types of supporting work (non core business) to become core work (core business) by using outsourcing and supporting systems (non core business) by the Business Sector Association in creating the flow of activities to determine for themselves the type of core work (core business) so that there would be an efficiency and optimization of the core business activities of a company.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".