Assessing Safety Culture with the Help of an Innovative Dedicated Interpretation Tool
Bibliographic record
Abstract
Assessing Safety Culture with the Help of an Innovative Dedicated Interpretation Tool Philippe Blanc; Philippe Blanc Total E&P Search for other works by this author on: This Site Google Scholar Thomas Montaudoin; Thomas Montaudoin Total E&P Search for other works by this author on: This Site Google Scholar Alain Lafaille; Alain Lafaille Total E&P Search for other works by this author on: This Site Google Scholar Ivan Boissières; Ivan Boissières ICSI Search for other works by this author on: This Site Google Scholar Marcel Simard Marcel Simard University of Montreal Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Conference on Health, Safety and Environment in Oil and Gas Exploration and Production, Rio de Janeiro, Brazil, April 2010. Paper Number: SPE-126591-MS https://doi.org/10.2118/126591-MS Published: April 12 2010 Cite View This Citation Add to Citation Manager Share Icon Share MailTo Twitter LinkedIn Get Permissions Search Site Citation Blanc, Philippe , Montaudoin, Thomas , Lafaille, Alain , Boissières, Ivan , and Marcel Simard. "Assessing Safety Culture with the Help of an Innovative Dedicated Interpretation Tool." Paper presented at the SPE International Conference on Health, Safety and Environment in Oil and Gas Exploration and Production, Rio de Janeiro, Brazil, April 2010. doi: https://doi.org/10.2118/126591-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search Abstract Significant safety performance improvement in high risk industry cannot be reached unless human and organizational factors are taken into account; this is a compulsory element of the successful implementation of a safety management system. Most of the time this is achieved through the assessment of a level or type of safety culture, performed through safety perception surveys, possibly completed by focus groups interviews. Generally such programs require specific expertise and sociological skills, most of which being external to the company.In order to ease such a process, TOTAL SA has developed a global safety culture assessment toolkit. The key element of this toolkit is an innovative computerized system to process and help the interpretation of data steming from safety culture perception surveys. User-friendliness of the software allows automatic delivery of indices and charts which enable to rapidly diagnose the key elements of safety culture in terms of strengths and weaknesses, and organized along a pattern of themes such as: Risk perception, Safety culture type beliefs, Organization and work context, Management leadership, Technical safety management, Behavioural safety management, Employees' behaviors, Employees' involvement, Employees' compliance, Work team / peers influence, and Ergonomics / Engineering. Additional Health and Environment themes lead to a SHE culture assessment.New 2-D diagrams are included, yielding safety culture signatures whick make it possible to undertake benchmarking between different organizations (companies, units, activities, sites, etc.). A statistical module is also proposed to measure consistency level of the responses.This new tool has been successfully applied in different entities of TOTAL group, either Exploration & Production affiliates or Refineries. Typical results are shown in this paper. In case additional interviews are deemed necessary to clarify some results, then the tool allows rapid and easy identification of the focus groups of people to be considered, as well as the topics to be preferentially discussed. The tool can be customized to any organization, safety culture model, questionnaire, themes, respondents' criteria, responses scales, etc. It is part of a global SHE management tools chain to reduce uncertainty in risk management. Keywords: graph, different category, perception index, data processing, interpretation, category, safety culture assessment, respondent, spe 126591, perception Subjects: Safety, Human factors (engineering and behavioral aspects), Safety risk management Copyright 2010, Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".