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Record W7027445912

Collaboration, Knowledge-Sharing and Natural Hazard Risk Management in the Greater Pinery Provincial Park Region

2021· article· en· W7027445912 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsNatural hazardHazardRisk managementNatural (archaeology)Natural disasterEnvironmental hazardRisk assessment
DOInot available

Abstract

fetched live from OpenAlex

In Canada, parks and other forms of protected areas are visited by tens of millions of people annually. By their very nature, parks and protected areas present various risks that must be mitigated. Risk management is an area of research that is receiving increased attention because in recent years, natural hazards (e.g. effects the environment) and disasters (e.g. effects the environment and humans) have exacted significant economic, social, health, cultural, and environmental impacts on persons and communities across Canada. Natural hazards, which pose significant risks to the natural environment and those individuals who inhabit or visit them, are expected to increase in occurrence and severity because of climate change. Knowledge and knowledge management is vital to making informed decisions that aim to protect the health and well-being of visitors. Understanding the value in and having the capacity to access and use various forms of knowledge (including social science, natural science, local, Indigenous, and other forms of knowledge) when making decisions to help proactively and reactively respond to natural hazard risks is critical now and in the future.\nThis thesis focuses on tornadoes and wind events in the greater Pinery Provincial Park region to understand the risks that these natural hazards pose to visitors and how to best adaptively mitigate such risks in the face of climate change. The thesis employed a qualitative case study approach, which examined how knowledge of natural hazard risk management is (or is not) used, produced, shared, and managed within the greater Pinery Provincial Park region. Informing the research study design were Nguyen et al.’s (2017) Knowledge-Action Framework and Bennett et al.’s (2016) Framework for Collaborative and Integrated Conservation Science and Practice. 15 key informants participated in semi-structured, in-person interviews, that were collaboratively coded using an adapted version of Braun and Clarke’s (2006) inductive, thematic approach, aided by NVivo 12 software, to discover 12 main themes, including: 1) Adaptive Management, 2) Collaboration and Partnerships, 3) Communication, 4) Knowledge Acquisition, 5) Knowledge Integration and Decision-making, 6) Knowledge Sharing and Exchange, 7) Planning, 8) Plans, Policies, and Regulations, 9) Relationships, 10) Resources and Capacity, 11) Responsibility and, 12) Risk Monitoring and Evaluation.\nThematic coding findings identified a number of diverse strengths (e.g., transparent internal communication and integration of natural science knowledge into decision-making), weaknesses (e.g., lack of collaboration and partnerships with Indigenous communities and an absent understanding of social science and its’ value), and needs and opportunities (e.g. involvement of Public Health sector stakeholders in natural hazard risk management and more dedicated resources to support capacity).\nThe Sendai Framework for Disaster Risk Reduction 2015-2030 was chosen to deductively frame the discussion. The goal of the Framework is to: “prevent new and reduce existing disaster risk through the implementation of integrated and inclusive economic, structural, legal, social, health, cultural, educational, environmental, technological, political and institutional measures that prevent and reduce hazard exposure and vulnerability to disaster, increase preparedness for response and recovery, and thus strengthen resilience” (UNDRR, 2015, p. 11). The Framework’s first three priorities focused on: 1) understanding disaster risk, 2) strengthening disaster risk governance to manage disaster risk, and 3) investing in disaster risk reduction for resilience, effectively guided the discussion of the 12 main themes identified from the key informant’s in-person interviews (UNDRR, 2015). The Framework’s fourth priority focused on enhancing disaster preparedness for effective response and to “Build Back Better” in recovery, rehabilitation, and reconstruction (UNDRR, 2015).\nNumerous detailed immediate-term and short-term recommendations, based on the 12 main themes identified through the inductive, thematic analysis, are put forward, including: 1) focusing efforts on proactive natural hazard risk management planning in anticipation climate change effects; 2) integrating social science knowledge, traditional ecological knowledge, Indigenous knowledge and other forms of knowledge more effectively into natural hazard risk management decision-making; 3) involving, more effectively, Public Health sector stakeholders in natural hazard risk management planning; and, 4) increasing availability and access to financial resources to support risk management activities. The implementation of such recommendations would support more effective adaptive natural hazard risk decision-making, planning and management in the region. Overall, the research study addresses a critical gap in parks and protected area and natural hazard research. It represents the first known study in Canada to examine how knowledge of natural hazard risk management is (or is not) used, produced, shared, and managed within a greater protected areas context.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.944
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.205
Teacher spread0.191 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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