Cultural Maturity Model: Health and Safety Improvement through Involvement
Bibliographic record
Abstract
Cultural Maturity Model: Health and Safety Improvement through Involvement Mark Fleming; Mark Fleming Saint Mary's University Search for other works by this author on: This Site Google Scholar Scott Meakin Scott Meakin Petro-Canada 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, Calgary, Alberta, Canada, March 2004. Paper Number: SPE-86623-MS https://doi.org/10.2118/86623-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Fleming, Mark, and Scott Meakin. "Cultural Maturity Model: Health and Safety Improvement through Involvement." Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. doi: https://doi.org/10.2118/86623-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search AbstractPetroleum companies increasingly recognize the importance of the cultural aspects of health and safety management. This is due in part to the conclusion that a poor safety culture contributed to a number of disasters. Many Petroleum companies have measured their safety culture in order to identify improvements. Questionnaires are commonly used, as they are an efficient method to collect large data sets that can be analyzed statistically. Unfortunately, safety culture surveys have limitations; for example, they provide little assistance in identifying interventions to address areas of concern. A potential solution to this limitation is the use of a maturity or evolutionary framework. In the UK the offshore oil industry and the Health and Safety Executive commissioned a study to develop a health and safety maturity framework1. The study produced a cultural maturity model based on capability maturity models used in the software industry. This framework is similar to Westrum's three level safety maturity model2. These and other models were used as the basis of a Canadian cultural maturity model. This model consists of 5 levels of maturity (Documenting, Controlling, Engaging, Participating and Institutionalizing) and 10 elements. This paper describes the development of the model and the results of a cultural maturity project conducted in Petro-Canada's East Coast Operations.IntroductionHigh hazard organisations (e.g. petrochemical, aviation, medicine) increasingly recognise the importance of the cultural aspects of safety management. This is due in part to the findings from investigations into major disasters in the petrochemical industry (e.g. Piper Alpha) and other industries such as nuclear power (e.g. Three Mile Island and Chernobyl), marine transportation (Exxon Valdese and Zeebrugge) and passenger rail transportation (Ladbrook Grove and Clapham Junction). The surprising thing about these investigations is that they all concluded that systems broke down catastrophically, despite the use of complex engineering and technical safeguards. These disasters were not primarily caused by engineering failure, but by the action or inaction of the people running the system. "The causes in each case were malpractices that had corrupted large parts of the socio-technical system" p2173.In parallel with the wider recognition of the importance of psychological aspects of safety, the concept of organisational safety culture came to the fore. The term 'safety culture' was introduced by International Atomic Energy Agency in their report on the Chernobyl nuclear power plant disaster in 1986 where the errors and violations of the operating procedures which contributed to the accident were seen by some as being evidence of a poor safety culture at the plant3. Safety culture has been described as the most important theoretical development in health and safety research in recent decades4. Although the importance of safety culture is widely accepted, there is still little agreement about what is meant by the term.To an extent, safety culture has been a victim of its own success, because the explosion of interest in safety culture has led to a range of conceptualisations, nearly one for each research team working in the area. A recent review of the research literature identified 16 separate safety culture definitions5. The issue is further confused by the related concept of safety climate. It appears that those who introduced the term safety culture ignored the earlier concept of safety climate described by Zohar6. Once the concept of safety culture became popular in the early 1990's the question of its relationship with safety climate arose. Over the last decade several attempts have been made to distinguish between the two terms (see Cox and Flin7), but safety climate is still often used interchangeably with safety culture. Keywords: safety culture, health, maturity, validity, safety climate, maturity model, participant, questionnaire, organisational factor, disaster Subjects: Safety This content is only available via PDF. 2004. 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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".