Culinary Clothing and Safety: Kitchen Uniforms as Personal Protective Equipment
Bibliographic record
Abstract
Chefs work long hours, often in the kitchen for 8 or more hours daily. While chefs are in this environment, they are exposed to many hazardous conditions including (but not limited to) contamination from raw meat and poultry, exposure to cleaning or pest control products, performing repetitive manual tasks, working in extreme temperatures, working with knives or other sharp equipment, risk of burns from ovens, deep fryers, steam and hot water, and slips, trips or falls (CCOHS, 2004). However, very little research has been done evaluating the effectiveness of personal protective equipment (PPE) and clothing utilized in the kitchen. While the uniform of a chef is quite standard, very little scientific evidence exists that this uniform is indeed effective in preventing against kitchen related accidents and injuries. Foodservice workers reportedly have one of the highest numbers of recordable injuries and illnesses, with the most common injuries being sprains and strains, cuts, burns and lacerations, and slips and falls (Personick, 1991). Burn injuries in food service workers were found to be mostly caused by coffee spills, grease splashes, and inadvertent bumps/contact with hot equipment (Halpin, Forst, & Zautke, 2008). Although ways to avoid these injuries was suggested, there was no mention of aprons or chef’s jackets and how they could be used to prevent against such burns. In another study, foodservice employees at one university were among a staff group that filed the highest number of accident/injury reports (Jaskolka, Andrews & Harold, 2008). Most of these injuries were due to being struck or caught by an object, slipping/tripping, and overexertion. Therefore, there is a clear need for more research to be done in regards to injury control and prevention and whether there is any potential for PPE to help lower accident rates, especially in the foodservice industry. This paper reports a study that examined the design, construction and effectiveness of the chef’s uniform as PPE in the kitchen environment.
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 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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".