Development of a Risk Perception Web Portal and Training Tool
Bibliographic record
Abstract
Development of a Risk Perception Web Portal and Training Tool Jan Dook; Jan Dook Centre for Learning Technology Search for other works by this author on: This Site Google Scholar Nancy Longnecker; Nancy Longnecker Centre for Learning Technology Search for other works by this author on: This Site Google Scholar Tim McGrath Tim McGrath The University of Western Australia 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-86840-MS https://doi.org/10.2118/86840-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Dook, Jan, Longnecker, Nancy, and Tim McGrath. "Development of a Risk Perception Web Portal and Training Tool." 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/10.2118/86840-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 AbstractRisk perception is a major contributing factor to incidents with root causes of failure involving human factors, accounting for up to 80% of incidents (Moore and Bea, 1993). Risk perception is a term widely used to include all the processes used by individuals to appraise and manage risk; it incorporates individuals' beliefs, attitudes and behaviour in relation to risk. Risk perception is determined by a range of factors, including internal motivations (eg risk avoidance, risk acceptance or risk taking), prior experience, assumptions about environmental conditions and the rate of change of the situation. Because it is difficult for an individual to predict their behaviour in hypothetical circumstances, it is best to measure risk perception in realistic situations; this is hard to set up and evaluate.In Stage 1 of this project, we propose to develop a Risk Portal - a Web-based risk perception environment with new resources and links to existing tools to measure risk perception as well as exercises and training for use by the international oil and gas industry. The Web-based environment will be constructed to allow update and addition by authorised organizations in order to build a library of resources that will keep pace with cognitive and behavioural psychology and experiences of the international oil and gas industry as well as other industries that are concerned with employee risk perception. Measurement of an individual's risk perception could generate an individually tailored training programme.In Stage 2 of this project, training will be developed for hazardous situations with the objective of allowing employees to mitigate risk by implementing appropriate barriers. The training will utilise multimedia presentation of case studies, interactive demonstrations and immersive simulation exercises set in the context of oil and gas industry operations. The training will be delivered in an interactive rather than linear manner so that each individual will have a unique and authentic experience as they explore the environment based on their own preferences. Support for this development is welcomed.IntroductionIn the oil and gas industry there is significant investment in the development of engineering solutions to minimise risk to an "as low as practicable" (ALARP) level, especially in those nations where a "Safety Case", non-prescriptive legislation, is utilised. To effectively mitigate the residual risk Safety Management Systems (SMS) are employed.Risk perception is a major contributing factor to incidents (Moore and Bea, 1993). There are numerous groups working to improve our understanding about risk perception of personnel in hazardous industries and particularly in the offshore oil and gas industry (eg see Crichton and Flin, 2001; Flin et al, 1996; Rundmo, 1992a; Slovic, 2000; Waring and Glendon, 1998). A Web-based portal is proposed to provide ready access to a library of current resources such as questionnaires, exercises and training in the area of risk perception.If risk perception can be measured effectively then it may be possible to investigate if training and experience affect risk perception and workplace safety. A pre-test will identify personnel's needs for training and a post-test will identify the effectiveness of the training. It may be identified that there is a decay rate over time that requires refresher training.Before undertaking a non-routine task, personnel need to firstly identify if an intolerable level of risk exists. Secondly, they need to assess the level of risk in terms of likelihood of occurrence and severity of the consequence. Thirdly, personnel must choose the most effective risk reduction method. Fourthly, as the task is being undertaken they must reassess the risk until either the task is completed or the task is stopped due to the risk becoming intolerable. Each of the four steps is dependent on personnel having enough data and experience to accurately assess risk and estimate the effectiveness of mitigation measures. One important factor is prior experience. Keywords: programme, risk management, university, educational technology, society of petroleum engineers, us government, risk perception, risk assessment, communication, information Subjects: Safety, Risk Management and Decision-Making, Professionalism, Training, and Education, Information Management and Systems, Risk, uncertainty, and risk assessment 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".