Dairy industry employee knowledge, attitudes and practices in response to COVID -19 policies in Jordan
Bibliographic record
Abstract
Purpose This study examined the level of knowledge, attitudes and practices (KAP) of Jordanian dairy employees about coronavirus disease 2019 (COVID-19) characteristics and the effect of precautionary measures on food safety risk during the pandemic. Design/methodology/approach A cross-sectional study was conducted between Dec 17, 2020 and Feb 22, 2021, involving a total of 428 participants across 34 random chosen dairy facilities in Jordan. KAP related to COVID-19 were measured by 46 items, while 13 items were used to examine perceived notions regarding COVID-19 precautionary measures on food safety. Findings The results indicated that 32.2% of the respondents had sufficient knowledge, 60.3% had a good attitude, and 27.1% followed correct practices concerning COVID-19. Moreover, female respondents had higher total KAP scores of COVID-19 characteristics than males. Furthermore, older and more experienced respondents had higher total KAP scores than younger respondents. This study also observed that the total KAP scores were not affected by education, marital status, and job position. Characteristics and measures taken by the dairy industry were at large significantly associated with ( p < 0.05) knowledge and practice of employees about COVID-19 attributes. Results of this study suggested that Jordanian dairy workers were not adequately aware about COVID-19. Originality/value No such study on dairy workers has been conducted previously to the best of the authors’ knowledge. Moreover, studies which analyse the association of industry response and characteristics on the KAP of employees are very limited.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".