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Record W4393860008 · doi:10.25071/pc5n3t08

Federalism, Disaster Planning Standards and Canadian Charter Rights

2023· article· en· W4393860008 on OpenAlexaffabout
Keith A. Fredin

Bibliographic record

VenueCanadian Journal of Emergency Management · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCharterFederalismEnvironmental planningPublic administrationPolitical scienceBusinessEnvironmental scienceLawPolitics

Abstract

fetched live from OpenAlex

Canada has a problem with emergency management (EM) standards. Canadians utilize a federalist government structure that pushes responsibility for EM planning from the federal government to provinces and territories, who then pass responsibility to municipalities (or regional counties) – who typically have less resources to engage in effective EM than higher levels of government (Raikes & McBean, 2016). In this structure, there are no set standards for levels of risk and disaster protection across the nation. The overall effect of this is the lack of protective measures and planning in place to provide the people living, working or visiting Canada to be as safe as they could be. For the purposes of this discussion, the definition of a disaster is any hazard that overwhelms a community’s ability to respond, where the hazard has an immediate and negative effect on tangible (lives, property and the environment) and intangible (cultural practice, knowledge and psychological well-being) assets (Coppola, 2020; Mysiak et al., 2016). Public Safety Canada (2017) has numerous documents, including ‘An Emergency Framework for Canada: Third Edition,’ that suggests all levels of government and citizens of Canada are responsible to be prepared and help mitigate disasters. Pragmatically, however, not all people have the means, opportunity, or privilege to be prepared (Cox & Kim, 2018). Furthermore, is it the responsibility of private citizens and businesses to be prepared in case of a large-scale natural or human-made disaster for which they have little resources, training, and control compared to governments? Federal, provincial and territorial (FPT) governments have the ability and responsibility, both morally and ethically, to institute more concrete disaster risk reduction (DRR) standards across the nation to ensure a higher level of safety for the people in Canada. DRR is described in line with the UN’s Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) (2015), where disasters are mitigated through reducing existing and future risk by investing in effective policy, legislation and the recognition of areas of inequality/vulnerability in society that typically lead to an increase of negative disaster outcomes. There is a variety of ways standards could be adopted by FPT governments, such as intergovernmental agreements (IGAs) or coercive or ‘strings attached’ federal funding (Rolland, 2022). Regardless, to date no standards have been created or adopted. As Raikes and McBean (2016) note, all but one province and territory—Québec, have little or nothing in their EM legislation that attempts to reduce risk through planning and preventative measures. Most provincial/territorial legislation only state that municipalities will develop and practice a plan; there are no or few specific guidelines, rules or frameworks for what should or should not be in EM plans; only that one should exist. This paper proposes greater research into interpreting the Canadian Charter of Rights and Freedoms (CCRF or the Charter) (1982) sections on the rights to life and security for EM, where insufficient legislation may leave FPT governments open to liability unless specific DRR standards are created and upheld to protect Canadians’ rights.

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)0.010
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.100
Threshold uncertainty score0.725

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0220.018
Scholarly communication0.0160.005
Open science0.0030.006
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0260.001

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 head0.056
GPT teacher head0.352
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes2
Has abstractyes

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