Analyzing Interrelationships Between Food Safety Practices and Inspections Among Food Staff in Manitoba
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The incidence and prevalence of food safety practices among food staff working in food establishments in Manitoba is underrepresented and has not been adequately reviewed and researched. Uncertified food staff are at higher risk of not following food safety practices that can cause contamination of food and result in foodborne illness. The purpose of this quantitative study was to determine the prevalence of food safety practices among food staff in Manitoba and to determine the relationship between food safety certification and routine health inspections. Pender's health promotion model and Bandura's social cognitive theory were used to explain the relationships and associations between variables. Archived data dating from 2012 to 2014 of health inspection reports on 558 food establishments were collected and analyzed using the Manitoba Health Hedgehog database. Chi Square, Pearson Correlation Coefficients, and Fisher's Exact Tests revealed the association of food safety practices, routine health inspections, and food safety certification. Results indicated no statistical difference between food safety practices and routine health inspections. Pearson's r analysis revealed a weak relation between routine inspections, internal temperature, thermometer use, and food storage/food protection noncompliance. Logistic regression analysis revealed that food safety certification was not a predictor of food safety practice compliance. This study can provide a bridge to reevaluate current health policies pertaining to food safety practices in Manitoba. This study adheres to the need for social change in establishing and creating prevention programs for food staff. Food safety programs can safeguard the food industry and protect public health from foodborne illnesses.
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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 | 0.001 |
| 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 it