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Record W4313567489 · doi:10.1177/028072700602400204

Risk Reduction and Emergency Preparedness Activities of Canadian Universities

2006· article· en· W4313567489 on OpenAlexaffabout
Kenton Friesen, Doug Bell

Bibliographic record

VenueInternational Journal of Mass Emergencies & Disasters · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsDillon ConsultingUniversity of Manitoba
Fundersnot available
KeywordsEmergency managementPreparednessPublic relationsPolitical scienceBusinessLegislationWorkforcePublic administrationLaw

Abstract

fetched live from OpenAlex

Preparing for emergencies and disasters has become a necessary part of daily operations of businesses, municipalities, and institutions. Furthermore, educational institutions such as universities, colleges, and schools are not immune to the impacts of disasters (FEMA 443, 2003; Kuban and MacKenzie-Carey, 2001; Miller, 2002; U.S. Department of Education, 2003). Universities are realizing they are exposed to the impact of disasters and that emergency/disaster response requires careful coordination and communication with other organizations and entities that have the resources and skills necessary to manage and respond to particular emergencies (Auf der Heide, 1989; FEMA 443, 2003; Kuban et al., 2001; Mileti, 1999). In Canada, the primary responsibility for emergency preparedness and response is that of the municipality, or local authority, within which a university is located. What then is the role of a university in preparing for and responding to emergencies or disasters? In the absence of compulsory standards, regulations or legislation, universities, based on the survey of this project, are nevertheless reviewing risks and hazards, implementing long-term strategies, and developing relationships with the local municipality. All of these should consider the unique characteristics of the campus environment, which include an open and accessible environment, a functionally separate hierarchy of administrators and academics, a multi-cultural and multi-disciplinary workforce, and a diverse student body, to name a few. After understanding the unique characteristics of the campus environment universities can address emergency preparedness and disaster management by building on the basics of existing and generally accepted standards, such as the NFPA 1600 (NFPA 2000). Additionally, many universities operate much like a municipality (i.e., infrastructure, constituents, and an incorporated government structure) making existing municipal emergency or disaster-related standards, regulations, and legislation also applicable. Further investigation into the application of these standards, regulations, and legislation to the university environment is required to validate the similarities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations12
Published2006
Admission routes2
Has abstractyes

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