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Record W2074511174 · doi:10.2118/137975-ms

Crossing Barriers In Language And Comprehension To Improve Worker Safety

2010· article· en· W2074511174 on OpenAlexafffund
Hugh Campbell, Alexandra Duguay, Christelle Lecoindre

Bibliographic record

VenueAbu Dhabi International Petroleum Exhibition and Conference · 2010
Typearticle
Languageen
FieldDecision Sciences
TopicRisk and Safety Analysis
Canadian institutionsTotal (Canada)
FundersUniversity of Toronto
KeywordsPictogramComputer scienceComprehensionUsabilityReading (process)GraphicsHazardHuman–computer interaction

Abstract

fetched live from OpenAlex

Abstract Transferring information that is critical to safe work is very difficult in culturally diverse work sites. Language and reading comprehension differs greatly from person to person, with increasing complexity when sharing information outside of the native language of the receiver. The challenge - to simplify the message while not diluting the salient points. The opportunity - creation of a short form material safety data sheet using pictograms and graphics rather than high amounts of text. The benefit - Higher degree of worker understanding and confidence resulting in lower incidents of near miss and injury on-site. Total Abu Al Bukhoosh (TABK) has launched a new short-form Material Safety Data Sheet (SMSDS) system that addresses pre-existing boundaries to effective communication of chemical hazards and risks. The pictorial form overcomes limitations of reading comprehension and language to ensure the highest degree of health and safety for our workers. The SMSDS is a single page, easy to read document that contains key information regarding the potential health effects, hazards and response measures of any particular chemical. The SMSDS was created by TABK in order to summarize the standard Material Safety Data Sheets while maintaining compliance with regulatory requirements. All with the aim of improving the usability of information made available to the end user of the chemical. In addition to the safety precautions that should be taken when working with the chemicals (e.g. wearing gloves, goggles or a masks etc.) another important issue that the SMSDS addresses is the correct response protocols that should be taken when a problem occurs, whether it is a spill, an accident or a fire. While kept within easy access of the work site, the information is also available online. The intranet database provides efficient management of information regarding the potentially hazardous materials in use at TABK, and offers a simple means to re-print sheets for convenience.

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)0.008
metaresearch head score (Gemma)0.041
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 score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0180.004

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 head0.020
GPT teacher head0.322
Teacher spread0.302 · 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".

Quick stats

Citations0
Published2010
Admission routes2
Has abstractyes

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