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Record W3136046110 · doi:10.47339/ephj.2020.31

An overview of the use of placards and the potential benefits for British Columbians

2020· article· en· W3136046110 on OpenAlexvenueaboutno aff
Pardip Dhaliwal, Environmental Health BCIT School of Health Sciences, Helen Heacock

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsnot available
Fundersnot available
KeywordsPublic healthAdvertisingMedicineInternet privacyBusinessPolitical sciencePublic relationsComputer scienceNursing

Abstract

fetched live from OpenAlex

Background: Environmental Health Officers (EHOs) are responsible for assessing the risk that food establishments pose to the public through regular inspections. The results of these inspections are then posted online for the public to view in British Columbia (BC). However, cities such as Toronto and New York City, have adopted the use of placards that are visibly placed at each food establishment, as well as posting the results online. The purpose of the placards is to provide a quick method for the public to ascertain the safety of food establishments. The use of placards has been shown to increase the compliance of food operators, as well as play a role in reducing foodborne illnesses. The purpose of this study was to determine if British Columbians would like to have the results of health inspections displayed on a placard in food establishments, in addition to them being posted online. Methods: An online, self-administered survey was created on SurveyMonkey Canada and distributed to residents of BC through Facebook and Reddit. The survey took approximately five minutes to complete and responses were collected over a nine-day period. The data was then analyzed using NCSS software. Results: From the 176 respondents, it was determined that approximately 44% of people knew about health inspection reports being posted online in BC, however, only 33% of people have visited health authority websites to view the inspections. 93% of the respondents would like to see a placard system implemented in BC. Furthermore, 72% of respondents would like to see a letter grade ranking of placards as opposed to a more general “Pass”, Conditional Pass” or “Closed” system. Results indicated a statistically significant association between the desire for a placard system and selecting a restaurant to eat at (p=0.000). Whether or not one views an online inspection report had no bearing on whether a placard system was desired. (p = 0.231). There is no association between age of BC residents and the preference for placards in BC (p = 0.618). However, there was an association between the age of respondents and knowledge of online reports of health inspections (p = 0.008), indicating that younger people are less likely to know about online health inspections that older populations. Conclusion: The results of this research study indicated that residents of BC overwhelmingly support the use of placards. BC residents would also like to see a letter grade placard system implemented. Although BC residents would like to see placards in food establishments, further research is required to assess what food operators, as well as other EHOs, think about implementing a placard system in place in food establishments.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.032
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.137
GPT teacher head0.254
Teacher spread0.117 · 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
Published2020
Admission routes2
Has abstractyes

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