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Record W4252320606 · doi:10.2523/86743-ms

Using Employee Risk Identification Reports to Measure Safety Performance and Set Safety Priorities

2004· article· en· W4252320606 on OpenAlexaboutno aff
R. Dickes, T. Wood

Bibliographic record

VenueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production · 2004
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsnot available
Fundersnot available
KeywordsCitationIdentification (biology)Computer scienceBusinessOccupational safety and healthWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

Using Employee Risk Identification Reports to Measure Safety Performance and Set Safety Priorities R. Dickes; R. Dickes Schlumberger Search for other works by this author on: This Site Google Scholar T. Wood T. Wood Schlumberger 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-86743-MS https://doi.org/10.2118/86743-MS Published: March 29 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Dickes, R., and T. Wood. "Using Employee Risk Identification Reports to Measure Safety Performance and Set Safety Priorities." 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/10.2118/86743-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 AbstractEmployee risk reports are a valuable part of a safety program. Managers frequently encourage employees to identify, correct, and report risks they discover while performing their jobs. The efforts by managers can have an immediate impact on safety performance by reducing or eliminating hazards in the workplace. However, the additional benefits that can be gained if employee reports are routinely analyzed for trends are often not realized.If these reports are analyzed, they provide constant and valuable feedback. This feedback can be used to detect negative trends and set priorities for future actions and improvements. In addition, reporting the results of an analysis to employees can increase employee participation in the risk-reporting system.The case study described in this paper shows the positive benefits achieved through risk-report analysis over a 2-year period. The feedback from this analysis was used to set priorities and was reported directly to employees, resulting in a more than 30% increase in employee risk reporting.IntroductionBeginning in the late 1980s, one major oilfield service company started programs to encourage employees to identify hazards they encountered at work, and to share this information with coworkers. The methods used to collect and share this information were informal systems managed at each operating location. However, within a decade the company developed a reporting system1 that enabled an employee to report a hazard and share it with coworkers worldwide.The introduction of a worldwide reporting system not only enabled information sharing, but also created an opportunity for managers to use this employee feedback to identify trends and set priorities worldwide. To do this, we completed a systematic review of the reports pertaining to ionizing radiation submitted during the period from January 1, 2001 through December 31, 2002.Completing this review, we detected several important facts. The radiation safety category covers a wide range of possible topics. In spite of this, employee reports centered on eight key topics or subcategories, with three subcategories dominating. A regional analysis of the data showed worldwide consistency in the reports. Within each of three regions, the eight subcategories and the three dominant subcategories were consistent, and employees submitted reports in nearly equal percentages in each subcategory.Company management incorporated these important discoveries into decisions when setting priorities for their radiation safety program. The company communicated these priorities to its employees and this feedback resulted in a 30% increase in the number of reports.History of Risk ReportingSafety risk reporting is a process to encourage employees to report to their supervisors and managers the risks they identify while performing their jobs. Risk reporting within the oilfield service company began in the late 1980s as field employees began reporting hazardous or unsafe conditions during the course of jobs being conducted on offshore drilling platforms. This process was primitive compared to the system used today. The information was simply captured on a piece of paper and submitted to the facility manager. Even though there was no official means of capturing, analyzing, or disseminating this information, safety managers realized the potential value of these risk reports. Safety managers generally agreed that two potential benefits existed:Accidents could be reduced when unsafe conditions were eliminated, before they resulted or contributed to an accident.Accidents could be reduced when employees learned valuable lessons from the risk reports made by other employees, and could take proactive steps to identify and either resolve or mitigate the unsafe condition at other locations.By the early 1990s, a concerted effort began to standardize the report form with the introduction of what was known as the Risk Identification Report (RIR). Each field location was responsible for tracking, categorizing, and disseminating the information. Regional offices manually compiled and maintained this information from each field location. Keywords: employee report, society of petroleum engineers, risk assessment, risk management, database, measure safety performance, hazard category, subcategory, encourage employee, upstream oil & gas Subjects: Safety, Risk Management and Decision-Making, Professionalism, Training, and Education, 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.

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 imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.135
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0200.008
Science and technology studies0.0010.000
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.004

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.

Opus teacher head0.143
GPT teacher head0.391
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2004
Admission routes1
Has abstractyes

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