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Record W4393852323 · doi:10.25071/2ek7p160

Nature-Triggered Disasters and the Involvement of Armed Forces: Exploring a Civil-Military Collaborative Framework

2023· article· en· W4393852323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Emergency Management · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsYork UniversityUniversity of Manitoba
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Nature-triggered disasters have been causing havoc in Canada over the past decade. Although many of these hazards cannot be prevented (e.g., earthquakes), their impacts can be managed through judicious planning and by mobilizing national resources. Considering the relentless force of nature and the degree of anticipation and preparedness needed, Canadian civil and military institutions must synergize to optimally utilize human capital, knowledge, and financial resources. Both the Canadian Armed Forces (CAF) and civil society actors have emphasized the importance of enhancing adaptive capacity and reliance on the armed forces for disaster response. As such, frequent involvement in domestic responses diverts the CAF’s focus away from national and international security threats, underscoring a serious national concern. Against this backdrop, the present paper analyzes existing civil-military cooperative models in Disaster Management in Canada and the USA. Three objectives are set: a) to explore the armed forces’ main tenets and approaches to disaster and emergency management, b) to find similarities and differences in institutional and resource priorities (before and during the onset of extreme nature-triggered events), and c) to identify the best collaborative practices and modes of operation of stakeholders involved. Using a case study approach, a desktop review of policy papers and an event database for two large-scale disasters: one in the United States (Hurricane Katrina in 2005) and one in Canada (the 1997 Red River flood in Manitoba) was carried out. The results offered the following major findings: a) organizational and cultural differences between the civil and military authorities in both countries drive the nature of disaster management; b) centralization vs. resource decentralization has remained the key factor in speeding up disaster response; c) political and legal scope and limitations in civil-military cooperation are often blurred; and d) the sole application of the Command, Control, and Communication (C3) approach becomes problematic when a multi-stakeholder approach is preferred for disaster management.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.249
Teacher spread0.216 · 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