Development of a Risk-Control Safety Program as an Architectural Contractor Guideline on Flats Project
Bibliographic record
Abstract
Construction Safety Planning is an element in the CSMS (Construction Safety Management System), which needs to be developed by the Contractor. Irrespective of this condition, the guidelines for preparing a safety program have not been appropriately disseminated by the project owner. This shows that many contractors are yet to appropriately implement the construction safety program. Therefore, this study aims to develop a safety program for Indonesian flat projects, especially architectural work. A qualitative method and secofndary data were used and obtained from a literature review, respectively. This was to determine the breakdown structure of architecture, which was then identified by hazards and operational risks. These processes led to the acquisition of the risk control used in preparing safety program targets, regarding resource analysis. The results showed that the resources needed in this architectural program included safety signs, PPE, warehouse construction, and transportation carts, which should be completed before work inception. In this case, an individual needs to be responsible for all the operational processes, namely the Safety Inspector/Supervisory Officer. These results are expected to be used as a guideline for contractors and project owners, to prepare a safety program and monitor the implementation of CS (construction safety).
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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".