Safety Pact
Bibliographic record
Abstract
Abstract This document describes the journey taken over the years by the Milazzo Refinery, together with the Contractors, to achieve and maintain levels of excellence for the health and safety of all workers. The last step in this process was the "Safety Pact" between all parties involved in health and safety aspects. The Pact is updated and renewed every year with increasingly challenging objectives. The Pact is based on the following innovative methods:STOP - ANALYZE - THINK - DO procedure. It is based on the self-evaluation risk which is a procedure that every employee has to follow before starting any activitySafety "Pills". Short meetings take place on the contractors working area aimed at analyzing good or and bad practice observed during the works executionHousekeeping Coordinator. New role dedicated to manage all the issues related with the housekeeping of the working areasRewarding system to evaluate behaviours adopted in the working area: bonus/malus points to workers depending on their particular attention for safety. The Safety Pact was thought and implemented as a first field test during a Major Turnaround (TA) and as a possible innovative tool to define rules and goals between RAM and Contractors, with the purpose of improving safety during turnaround activities and achieving the most important target of ZERO INJURIES. Following turnaround completion RaM and Contractors make a balance of the results analyzing performance index and making plan to improve weak area in the future. The implementation of a formal signed Safety Pact between RaM dramatically increased engagement of different companies (client + contractors) towards safety and allowed RaM to achieve ZERO INJURIES during the Turnaround activities. Moreover it has been observed an improvement of the housekeeping, a reduction of non-compliances for dangerous behaviour and a widespread application of RaM procedure for scaffoldings. The success of this kind of approach suggested RaM to adopt the safety pact to every refinery turnaround (both major and minor ones) but also extend it to each single refinery maintenance activity.
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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.151 | 0.063 |
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".