Background Factors Affecting the Implementation of Food Safety Management Systems
Bibliographic record
Abstract
A peer-reviewed article Why don’t workers follow Hazard Analysis Critical Control Point (HACCP) guidelines? Socio-psychological models have been used to describe factors that influence the implementation of food safety management systems (FSMSs) in food processing facilities. The theory of planned behavior posits that perceived control over one’s own behavior, one’s attitude and the influence of others are antecedents of behavioral intention and/or behavior. The objectives of this study were to identify background factors that influence food safety behaviors of production workers in small and medium sized meat processing facilities and examine how these factors are applicable to the theory of planned behavior. Using a qualitative approach, the researchers conducted 13 in-depth interviews at five meat plants and two focus group interviews with representatives of government and industry agencies. These interviews generated 219 single-spaced pages of verbatim transcripts, which were analyzed by use of NVivo 7 software. Ten themes found in the data relate to elements in the theory of planned behavior that were demonstrated to be applicable to a meat processing establishment. Confirmation of factors having the strongest influence on production workers in meat plants may assist in developing targeted interventions that improve the implementation of FSMSs in the meat and other food processing sectors.
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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 | 0.000 | 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".