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Record W3138747425 · doi:10.47339/ephj.2020.28

Individual emergency preparedness survey among Canadians in Lower Mainland, BC

2020· article· en· W3138747425 on OpenAlexvenueaboutno aff
Eric Yam, Environmental Health BCIT School of Health Sciences, Dale Chen

Bibliographic record

VenueBCIT Environmental Public Health Journal · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsPreparednessEmergency managementMedicineMedical emergencySuicide preventionNatural disasterEnvironmental healthPoison controlDemographyGeographyPolitical science

Abstract

fetched live from OpenAlex

Background: BC residents are prone to natural disasters and emergencies such as earthquakes and prolonged power outage due to severe weather and flooding. To minimize and mitigate the impacts, individuals should prepare in advance for any potential emergencies. There are studies showing only half of the Canadians, in general, are well prepared. Concrete evidence of factors affecting individual’s emergency preparedness are not clear. Therefore, this research study aims to investigate the association between BC residents’ emergency preparedness level and demographic/socio-economic factors. Methods: Housed on SurveyMonkey, the online self-administered survey was distributed via Facebook and Reddit to survey local BC residents. The survey was posted on sub-groups based on topic-relevance and geographic areas that are located within Lower Mainland. The sampling period is approximately one month, which the results were analyzed by the NCSS program. Results: Overall, less than half (41%) of the participants reported to have an emergency kit at home. The chi-square test results show that two factors, language (p=0.025) and status of occupancy (p=0.048) are significantly associated with level of emergency preparedness. Conclusion: There are significant associations between level of emergency preparedness and demographic factors - language barrier and status of occupancy. People who do not use English as their primary language found to be less prepared to those who use English as their primary language. Renters, as compared to homeowners, found to be less prepared as well. This serves as supporting data and evidence to transit these findings to promote emergency readiness among residents in Metro Vancouver.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.058
GPT teacher head0.298
Teacher spread0.240 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes2
Has abstractyes

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